Apple Inc. v. Samsung Electronics Co. Ltd. et al

Filing 562

EXHIBITS re #559 Declaration in Support, filed byApple Inc.. (Attachments: #1 Exhibit 4.02, #2 Exhibit 4.03, #3 Exhibit 4.04, #4 Exhibit 4.05, #5 Exhibit 4.06, #6 Exhibit 4.07, #7 Exhibit 4.08, #8 Exhibit 4.09, #9 Exhibit 4.10, #10 Exhibit 4.11, #11 Exhibit 4.12, #12 Exhibit 4.13, #13 Exhibit 4.14, #14 Exhibit 4.15, #15 Exhibit 4.16, #16 Exhibit 4.17, #17 Exhibit 4.18, #18 Exhibit 4.19, #19 Exhibit 4.20, #20 Exhibit 4.21, #21 Exhibit 4.22, #22 Exhibit 4.23, #23 Exhibit 4.24)(Related document(s) #559 ) (Jacobs, Michael) (Filed on 12/29/2011)

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espacenet - Bibliographic data

Page 1 of 1

INFORMATION PROCESSOR
Patent number:
Publication date:
Inventor(s):

JP7057103 (A)
1995-03-03
IDE YUJI; SASUGA MITSUO; TAKASHIMA KAZUHIRO; MOROHOSHI TOSHIHIRO;

Applicant(s):

TOSHIBA CORP +

NAKAJIMA KOJI +
Classification:

- international:

GO6F3/033; GO6F3/038; GO6T1/00; GO6T7/20; GO6T9/20; GO6F3/033; GO6T 1/00;
GO6T7I20; GO6T9/20; (IPC1-7): GO6T9/20; GO6F3/033; GO6T1/00

- european:

Application number: JP19930207358 19930823
Priority number(s): JP19930207358 19930823
Abstract of JP 7057103 (A)
PURPOSE:To place the information processor in

operation by operator's operation at a specific

position by picking up an image of the specific
position of the operator by an image pickup means,
recognizing the shape or position of the contour, and
performing control by using the result.
CONSTITUTION:When the operator 27 points his or
her index finger 25 at a display screen 22, a cursor
26 is displayed on the display screen 22
corresponding to the position of the tip of the index
finger 25. An image pickup lens 23 has sha llow
depth of field; and only a range of about 5-25cm
from the front surface of the lens is put in focus and
a subject which is a >25cm away becomes out of
focus. Namely, an image of the hand including the
index finger 25 is picked up in the in-focus state and
a background image 28 of the head 27 of the
operator 27 behind i t and others is picked up in an
out-of-focus state. The part of the hand 35 of the
operator is in focus, so an image signal of the hand
includes a high-frequency component and the

contour is sharp, but an image signal of the face 27
and background 38 includes no wide-range
frequency component, so the contour is not sharp.

Data supplied from the espacenet database - Worldwide

http://v3.espacenet.com/publicationDetails/biblio?DB=EPODOC&adjacent=true&local =en... 2/5/20 10
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espacenet - Bibliographic data

Page 1 of 1

CURSOR MOVEMENT CONTROLLER
Patent number:

JP6332620 (A)

Publication date:

1994-12-02

Inventor(s):
Applicant(s):

KAKO MITSUMASA; YAMAMOTO KOUJIROU +
BROTHER IND LTD +

Classification:

- international:

GO6F3/047; GO6F3/03; GO6F3/033; GO6F3/038; GO6F3/041; GO6F3/03; GO6F3/033;
GO6F3/041; (IPC1-7): GO6F3/033; GO6F3/03

- european:

Application number: JP19930146931 19930525
Priority number(s): JP19930146931 19930525
Abstract of JP 6332620 (A)

P(JRPOSE:To provide the cursor movement
controller which can move quickly and remarkably a

cursor on a display, when a playing input operation

is executed on a panel switch and can improve the
operability of a cursor movement thereby.
CONSTITUTION:When a depressing operation is
executed with a finger, etc., on a panel switch,
whether its depressing operation was executed by a
regular depressing operation, or executed by a
playing-up operation, is decided (S10 to S22), and
when it is decided that the depressing operation was
executed by being accompanied with the playing-up
operation, this controller is constituted so that an
interruption processing is executed, while increasing
gradually a timer set time set to each X direction
timer and Y direction timer, based on an average
moving speed in the X direction and the Y direction
of each point in an end point groove, and also, a
cursor is stopped on a CRT display when the timer
set time becomes a prescribed set value or below.

Data supplied from the espacenet database - Worldwide

http://v3.espacenet.com/publicationDetails/biblio?DB=EPODOC&adjacent--true&loca e=en... 2/5/2010
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espacenet - Bibliographic data

·

I age 1 of 1

WORK-SURFACE SYSTEM AND REALIZING METHOD THEREOF, SENSOR
UTILIZING METHOD AND PERSON IDENTIFYING METHOD
Patent number:

JP6083523 (A)

Publication date:

1994-03-25

( EPO546704 (A2)

Inventor(s):

TOOMASU EICHI SUPilTAA +

Applicant(s):
Classification:
- international:

AMERICAN TELEPHONE & TELEGRAPH +

1 EPO546704 (A3)
i JP9069021 (A)
i CA2203297 (A1)
i CA2078607 (A1)

GO6F3/047; GO6F3/033; GO6F3/041; GO6F3/048; GO6K9/00;

Also published as:

GO6T7/00; GO7C9/00; GO6F3/033; GO6F3/041; GO6F3/048;
GO6K9/00; GO6T7/00; GO7C9/00; (IPC1-7): GO6F3/03;
-european:

GO6F3/03; GO6F15/62
GO6F3/041; GO6F3/033; GO6F3/041F; GO6K9/00H;
GO7C9/00C2D

Application number: JP19920352427 19921211

Priority number(s): US19910807524 19911213

Abstract of JP 6083523 (A)

PURPOSE: To provide a method and device for
realizing an intelligent work surface.

CONSTITUTION: A work surface such as a disk top
or a floor is covered with a tactile sensing array 1
which supplies tactile sense data to a processor 2.
An area on the sensing array 1 is normalized so that
the prescribed segment element of the sensing
array 1 can be included, and set so as to be
functioned as an input device 5 such as a keyboard

3 or a mouse. The area can be re- normalized even
after normalized in order to rearrange the specific
input device. The area can be re-normalized so as
to be functioned as a different input device. The
array 1 collects data in a prescribed interval for the
purpose of analysis such as the identification of an
individual or an object. For example, the image of
force such as the hand print or foot print of the
individual is collected, analyzed, and compared with

data indicating the image of the force corresponding
the known individual.

Data supplied from the espacenet database - Worldwide

http://v3.espacenet.com/publicationDetails/biblio?DB=EPODOC&adjacent=true&loca e=en... 2/5/2010
APLNDC00021774

Europäisches Patentamt
European Patent Office

Office européen des brevets

Publication number:

0 546 704 A2

EUROPEAN PATENT APPLICATION
Application number: 92310595.1

Date of filing: 20.11.92

A request for correction of the numbering of
claims number 29 as to read number 28 has
been filed pursuant to Rule 88 EPC. A decision
on the request will be taken during the
proceedings before the Examining Division
(Guidelines for Examination in the EPO, A-V,
2.2).

@ Int. CI.E GO6F 3/033, GO7C 9/00,

A61 B 5/117

Applicant: AMERICAN TELEPHONE AND
TELEGRAPH COMPANY
32 Avenue of the Americas
New York, NY 10013-2412(US)

Inventor: Speeter, Thomas H.
429 Ely Harmony Road
Freehold, New Jersey 07728(US)

Priority: 13.12.91 US 807524

Date of publication of application:

Representative: Johnston, Kenneth Grah am et

16.06.93 Bulletin 93/24

al
AT&T (UK) Ltd. 5 Mornington Road

Designated Contracting States:

Woodford Green Essex, IG8 OTU (GB)

DE FR GB IT SE

Intelligent work surfaces.
Methods and apparatus for implementing intelligent work surfaces are provided. Work surfaces,
such as desktops and floors, are covered with a
tactile sensing array to provide tactile data to a
processor. Regions on the sensing arrays may be
defined to include predetermined sensing elements
of the sensing array and may be specified to function as input devices, such as a keyboard, a mouse,
or the like. Once defined, regions may be redefined
to reposition a specified input device. Regions also
may be respecified to function as a different input
device. The arrays also may collect data at predetermined intervals for analysis, such as for identifying
an individual or an object. For example, the forceimage of an individual's handprint or footprint could
be taken, analyzed, and compared against data representing the force-images of known individuals.

FIG. 2
6

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APLNDC00021792

Europäisches Patentamt
European Patent Office

Office européen des brevets

Publication number:

0 546 704 A2

EUROPEAN PATENT APPLICATION
Application number: 92310595.1

Int. CI.6: GO6F 3/033, GO7C 9/00,

A61B 5/117
Date of filing: 20.11.92

A request for correction of the numbering of
claims number 29 as to read number 28 has

Applicant: AMERICAN TELEPHONE AND
TELEGRAPH COMPANY

been filed pursuant to Rule 88 EPC. A decision
on the request will be taken during the
proceedings before the Examining Division
(Guidelines for Examination in the EPO, A-V,

32 Avenue of the Americas

2.2).

New York, NY 10013-2412(US)
Inventor: Speeter, Thomas H.
429 Ely Harmony Road
Freehold, New Jersey 07728(US)

Priority: 13.12.91 US 807524
Date of publication of application:
16.06.93 Bulletin 93/24
Designated Contracting States:
DE FR GB IT SE

Representative: Johnston, Kenneth Graham et
al
AT&T (UK) Ltd. 5 Mornington Road
Woodford Green Essex, IG8 OTU (GB)

Intelligent work surfaces.

N

Methods and apparatus for implementing intelligent work surfaces are provided. Work surfaces,
such as desktops and floors, are covered with a
tactile sensing array to provide tactile data to a
processor. Regions on the sensing arrays may be
defined to include predetermined sensing elements
of the sensing array and may be specified to function as input devices, such as a keyboard, a mouse,
or the like. Once defined, regions may be redefined
to reposition a specified input device. Regions also
may be respecified to function as a different input
device. The arrays also may collect data at predetermined intervals for analysis, such as for identifying
an individual or an object. For example, the forceimage of an individual's handprint or footprint could
be taken, analyzed, and compared against data representing the force-images of known individuals.

FIG. 2
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APLNDC00021793

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EP 0 546 704 A2

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Field of the Invention

Summary of the Invention

The present invention relates to tactile sensor
arrays and, more particularly, to methods for using
tactile sensor arrays to implement work surfaces.

Tactile sensing arrays may be configured and
monitored to create "intelligent" work surfaces having the versatility and adaptability to be configured
to receive information and to implement various
input and telecommunications devices. Intelligent
work surfaces can be reconfigured at will to implement different devices. Moreover, these surfaces
can be reconfigured to change the location and
orientation of the devices.
Intelligent work surfaces can be implemented
as intelligent desktops, floors, walls, or other such
surfaces. In a preferred embodiment, the intelligent
surface is a desktop surface capable of implementing input and telecommunications devices such as
a keyboard, numeric keypad, mouse, and the like.
An intelligent desktop also can monitor the presence and location of items on the desktop. Inputs
to the the intelligent surface produce outputs from
the tactile array which are interpreted as outputs
from the implemented device. Devices implemented on the intelligent desktop surface preferably are
implemented as templates, and therefore do not
occupy and clutter valuable workspace. Implemented devices may be arranged and rearranged on the
work surface to suit different users and changing
workspace requirements. There are no computer
cables to tangle or to restrict device placement.
In another embodiment, intelligent work surfaces are implemented as floor surfaces. Intelligent
floors are capable of detecting the presence and
tracking the location of objects and people on the
surface. In still other embodiments, the surface is
configured to produce a two-dimensional image of
the forces applied to the surface (a "force-image")
for identifying a person. For example, the forceimage of a person's handprint can be sampled,
analyzed, and compared against data representing
the force-images of known individuals to identify
the person creating the handprint.

5

Background of the Invention
Many offices and laboratories are equipped
with computer and telecommunications systems.
These systems require a variety of input devices,
such as keyboards, mice, telephones, and facsimile
machines, which occupy and clutter valuable workspace. The various input devices are not as convenient as they could be. For example, it often is
difficult to rearrange input devices on a work surface. Many input devices, such as the keyboard
and mice described above, are connected to a
computer system by cables and therefore are restricted in position. It also may be difficult or inconvenient to move or reorient such devices to accommodate different computer users or changing
space requirements.
One prior art technique for consolidating input
devices was to provide an array that performed
different functions at different times. For example, a
computer keyboard typically includes an array of
keys that may be defined as a numeric keypad at
one time and may be defined as cursor control
keys at another time. However, such input deviceS
do not permit the array itself to be reconfigured to
provide an entirely different function, such as a
mouse. Also, the input device could not be reconfigured to change the position or orientation of the
array on the device.
Other desirable functions such as inexpensive,
simple, and reliable security for an unsecured office or laboratory are unavailable. One possible
example of a need for such security would be the
ability to monitor the presence of objects on a
laboratory surface. For example, it may be important to know whether chemicals or experiments in a
laboratory have been touched, moved, or otherwise
tampered. Similarly, it may be important to know
whether objects in an office were touched or
moved.
Security measures limiting access to secured
areas or to computer systems also may be improved. Security measures such as combination
locks and computer passwords may not provide
the level of security desired. For example, it may
be desirable to replace or augment combination
locks and passwords with other security measures
that are not easily circumvented such as by discovery by unauthorized personnel.

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Brief Description of the Drawings

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The above and other advantages of the invention will be apparent upon consideration of the
following detailed description taken in conjunction
with the accompanying drawings in which like reference numbers refer to like parts throughout and
in which:
FIGs. 1 and 2 are perspective views of a desktop surface covered with sensing arrays configured as an intelligent work surface in accordance with the principles of the invention;
FIG. 3 is a simplified, partial exploded view of
the intelligent work surface of FIG. 2;
FIG. 4 is a block diagram of circuitry for implementing intelligent work surfaces according
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to the principles of the present invention;
FIG. 5 is a flowchart for implementing a
keyboard-type interface on an intelligent desktop
surface;
FIG. 6 is a flowchart for implementing a mousetype interface on an intelligent desktop surface;
FIG. 7 is a flowchart for implementing an imagetype interface on an intelligent desktop surface;
FIG. 8 is a flowchart for identifying a individual
on the basis of a handprint by using an intelligent desktop surface;
FIGs. 9 and 10 are plan views of an image of a
handprint generated on the intelligent work surface;
FIG. 11 is a flowchart for controlling a mobile
vehicle using an intelligent floor surface;
FIG. 12 is a flowchart for using an intelligent
floor surface to identify an individual using footprint analysis; and
FIG. 13 is a graph of data from successive
footprint image samples.

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Detailed Description
Tactile sensing arrays may be configured and
monitored to create "intelligent" work surfaces to
implement various input and telecommunications
devices, such as a keyboard, a numeric keypad, a
mouse, or the like. Inputs to the intelligent surface
produce outputs from the tactile array which are
interpreted by a processor as outputs from the
implemented device. For example, force applied to
the tactile array produces an electrical signal at the
outputs of the array. The processor then interprets
the electrical signal as a keystroke output from a
keyboard. When a particular device is no longer
needed or when a new device is desired, the
intelligent work surface is reconfigured to implement different devices. For example, the intelligent
work surface can be reconfigured such that outputs
from the tactile array in the example above are
interpreted as outputs from a mouse to a display
screen instead of keystrokes from a keyboard.
Implemented devices may be arranged and
rearranged on the work surface to suit different
users and changing workspace requirements. For
example, a keyboard is configured at a first location by a first computer user. The location of the
keyboard is shifted, for example, to the left to
accommodate the preferences of a subsequent
computer user.
FIG. 1 shows a desk entirely covered with a
tactile array surface 1 and a processor 2. FIG. 1
also shows a keyboard 3, a numeric keypad 4, an
input interface 5, and a display screen 6. Tactile
array 1 is coupled to processor 2 to form the
intelligent work surface system. Tactile array 1
outputs to the processor information about inputs

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SS

4

applied to the array. Groups of sensing elements
(see FIG. 3) which make up the tactile array are
configured as an input interface to implement various devices. For example, groups of sensing elements of tactile array 1 are configured as a keyboard interface 3. As used herein, the term
"region" refers collectively to a group of sensing
elements on array 1. In a typical application, force
applied to predetermined sensing elements within
the region of the tactile array configured as keyboard 3 will generate signals indicative of keystrokes. Similarly, other groups of sensing elements of tactile array 1 are defined, for example, to
be numeric keypad 4 or to be input interface 5 for
display screen 6.
Input interfaces or devices implemented on
tactile array 1 can be reconfigured at will to change
the location, size, or orientation of the devices.
Also, new devices may be configured on the tactile
array and existing devices may be removed. For
example, FIG. 2 shows keyboard 3, keypad 4, and
display input interface 5 reconfigured to have a
new location on tactile array 1. Reference numbers
3', 4', and 5' indicate the prior location (shown in
phantom) corresponding to the position shown in
FIG. 1, of each device. The groups of sensing
elements identified by 3', 4', and 5' have been
reset to their original state (which typically may be
undefined). The portion of the tactile array having
sensing elements 3' which overlaps with keyboard
3 is redefined to perform the appropriate functions
for keyboard 3.
FIG. 3 shows the sensing elements 7 which
form tactile array 1. Sensing elements 7 are formed
by the intersection of rows and columns of electrical conductors. Inputs (i.e., forces) applied to
tactile array 1 cause the row and column conductors to contact. Contact of the conductors permits
electrical current to flow, thus generating an output
from the sensing element located at the intersection of the row and column conductors.
As shown in FIG. 3, region of tactile array 1
defined by processor 2 as numeric keypad 4 overlays selected ones of sensing elements 7. Processor 2 performs a "template" function by defining a
group of sensing elements as an input device, in
this case, the numeric keypad. Processor 2 also
performs a "mapping" function to interpret the outputs of the sensing elements as outputs of the
defined input device. For example, keys "1" and
"4" of keypad 4 overlay the groups of sensing
elements which are designated collectively by reference numbers 8 and 9, respectively. Processor 2
will interpret outputs from sensing elements 8 and
9 (resulting from force applied to those elements)
as outputs of keypad 4.
Numeric keypad 4 may be repositioned by
changing in processor 2 the definition of the region
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on tactile array 1 which corresponds to the keypad.
Redefining the region is accomplished in this example by specifying different ones of sensing elements 7 to function as the keys of keypad 4. For
example, keypad 4 may be redefined by processor
2 such that key "1" of the keypad overlays the
group of sensing elements designated by reference
number 9 (i.e., instead of the sensing elements
designated by reference number 8, as shown in
FIG. 3). Keypad 4 is shifted downward so that key

n

ment an intelligent work surface (i.e., tactile array 1
of FIG. 1) or a plurality of such work surfaces.
Addressing circuitry 14 is associated with each
sensor array 12, for addressing the individual sensing elements (also referred to as "pixels" or
"taxels") which form each array 12. Circuit 14 is
shown as an application specific integrated circuit
or "ASIC." Analog to digital (A/D) conversion circuitry 16 (having sample and hold capability) receives data outputs passing through addressing
circuitry 14 from array 12. After a predetermined
settling period (determined by the array characteristics), data pass from the A/D converter to a data
bus 20 via an addressable tri-state buffer 18. Data
bus 20 couples to an appropriate processor such
as processor 2 in FIGs. 1 and 2 for processing data
in accordance with the principles of the invention.
Implementation details of the illustrative sensor array circuitry of FIG. 4 will be discussed further
following a discussion of illustrative techniques for
implementing intelligent work surfaces.
FIGs. 5-7 flowchart illustrative methods for implementing various desktop applications in processor 2. FIGs. 11 and 12 flowchart illustrative methods for implementing various intelligent floor applications in a processor such as processor 2.
Before describing the various applications in
detail, two image processing techniques common
to most of the applications will be described. These
techniques are "connected region analysis" (or
"clustering") and determining the centroid of an
image. Clustering involves grouping sampled pixels
of array 12 into connected regions. Clustering techniques are well-known in the art of image processing, and are described in T. Pavlides, Algorithms
for Graphics and Image Processing, Comp. Science Press, 1982. The centroid of each clustered
region may be determined for an nxm sensor
array using the formulas:

m

i = -- E i i*Vij
i=1 j=1
5

1

n

m

ÿ = -- E y j * V ¡¡
nm i=1 j=1
10

"1 "occupies the location formerly occupied by key
"4," key "2" occupies the location formerly occupied by key "5," etc. As redefined, processor 2
will interpret the outputs of sensing elements 9 as
a output "1" from keypad 4, instead of the output
"4" as originally define
FIG. 4 shows several tactile sensor arrays 12
connected in parallel, which may be used to imple-

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where n and m are the numbers of rows and
columns in the sensor array, respectively, i and j
are the row and column displacement, respectively,
and V is the gray scale value of the pixel at
coordinates (i,j).
In a desktop application, data typically will be
input to a processor through one of three types of
interfaces: a "keyboard" interface, a "mouse" interface, or an "image" interface. Portions of the deskÍOp surface can be defined, through an initialization
procedure, to be input devices of one of these
types of interfaces. The processor defines input
devices by the template and mapping functions
described above. That is, the processor first identifies selected sensing elements as an input device.
The processor then interprets (maps) the outputs of
the selected sensing elements to be outputs of the
input device. The processor may define several
input devices simultaneously, on different portions
of the desktop.
Referring again to the figures, the flowchart of
FIG. 5 shows an illustrative method for implementing a keyboard interface. The keyboard interface
may be used to provide keyboards (such as keyboard 3 of FIG. 1), numeric keypads, and other
similar devices. (These devices may be constructed, for example, by overlaying a sheet of compliant
material with a patterned template.) As will be
described more fully below, the process illustrated
by FIG. 5 also is used to define other, non-keyboard devices.
As shown in box 30, a processor (such as
processor 2 of FIG. 1) samples sensor array 12.
This may be done, for example, by cycling through
the array to address each sensing element. Sampled points then are "clustered" into connected
regions, and the processor computes the centroid
of each region. Once the data is collected from the
array, the processor performs one of three general
operations. The processor either defines a device,
performs a processing operation for a device already defined, or performs an "optional" or special
processing operation upon the occurrence of some
predetermined event (e.g., contact to tactile array 1
outside of any defined region).
Boxes 32, 34, 36, and 38 show how a module
(i.e., a defined area on the sensor array or a device
such as a keyboard or mouse) may be added to a

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list of "active" devices. The array is sampled until
at least one cluster is detected. Upon detecting a
cluster, the processor determines whether there are
three clusters. If three clusters are detected, the
processor determines whether the pattern formed
by the centroids of the three clusters correspond to
the "footprint" of a known module. If so, the module and its position and orientation are added to a
list of active devices. If the centroids do not correspond to the footprint of a known module, the
inputs may be ignored, and the array is sampled
again.
Once a device is active, the processor monitors arrays to determine, for example, whether a
key is struck in the active region. If the response to
decision box 34 is "no" (i.e., the number of clusters does not equal three), the processor determines whether there is only one cluster (box 40)
and to which active device this cluster belongs
(box 44). Because each device is divided into nonoverlapping regions, the centroid of a single cluster
will reside in one region identifying, for example,
the "key" of the keyboard that was pushed.
Device-specific software running on processor 2
then interprets the outputs of the tactile array as
outputs of the defined input device and executes
functions on the basis of the detected keystrokes
(box 46).
If the decision at box 40 is "no," (i.e., there is
more than one cluster) the processor preferably
performs additional processing to act on multiple
contacts to the sensor array (box 48). This provides
a means for allowing module-independent functions, such as system on/off, last entry erasure,
session termination or restart, or region definition
for other module types (e.g., a mouse). Similarly, if
the answer to decision box to 42 is "yes," the
processor preferably performs additional processing (e.g., erasing previous key strokes of a calculation by striking outside an active calculator area)
for contacts outside the active region of any known

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module (box 50).
An illustrative flowchart for implementing on
tactile array 1 a second interface type, a mouse

device, is shown in FIG. 6. The mouse active
region (i.e., the sensing elements which define the
bounds of the device) must first be defined (box
50) on tactile array 1. This is done using the steps
illustrated by the flowchart of FIG. 5. The mouse is
then implemented by performing three distinct operations. First, an origin must be established in the
mouse region. The origin establishes a position of
a cursor on the screen of a display monitor. Second, click events must be detected and indicated.
A click event is an input to the mouse device which
indicates that a predetermined processing operation should occur. Third, the cursor on the screen
of the display monitor must be repositioned in

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response to repositioning of the origin in the mouse
region.
Having defined the mouse active region, the
tactile array is sampled until a cluster is detected in
the defined mouse region (box 52). Once a cluster
is detected, the processor determines whether an
origin has been established (box 56). If an origin
has not been established, processing continues as
shown in box 58. The processor samples the
mouse region of the sensor array several times.
The average centroid is calculated by adding the
centroid x and y values to a running total, and
dividing that running total by the number of samples taken. An origin is then marks A sample
counter may be used to ensure that a predetermined number of samples are taken (box 60). The
number of samples taken should exceed the number required to reliably locate the origin of original
contact. If the original cluster is not in the active
mouse region, the running total counters are reset
(box 54), the origin is not established, and the next
sample is taken.
Once an origin is established as described
above, the processor continues to sample the array. The processor determines for subsequent
samples whether the sum of the pixel values in the
cluster of each sample exceeds the "click threshold" (see box 64). The click threshold is a predetermined value over which it is assumed that a
mouse "click" event has occurred. Exceeding the
click threshold has the same effect as depressing
the buttons of a conventional mouse. Upon occurrence of a click event, the processor executes
instructions as required by a particular application
on occurrence of a click event (box 66). If the sum
of pixel values in a cluster does not exceed the
click threshold, the processor determines whether
the centroid of the cluster has been moved a
predetermined distance (the "origin distance") from
the centroid of the origin (box 68). If it has not, the
array is sampled again. If the centroid has moved a
sufficient distance, a cursor displayed on the
screen of an associated display monitor (not
shown) is moved to a new position prior to taking
the next sample (box 70). The cursor on the display monitor is moved in the direction from the
origin to the current centroid. The cursor is moved
a distance equal to the product of a "velocity
constant" and the distance between the origin and
the current centroid. The velocity constant depends
upon the sensor resolution, the resolution of the
display monitor, and the sampling rate, and preferably may be changed by a user to suit the user's
preference as to how fast the cursor should move.
Techniques for moving the cursor in response to
the new centroid are similar to techniques for moving a display cursor in response to movement of a
conventional mouse. These techniques are wellAPLNDC00021797

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known in the art.
The image interface is described with reference to FIG. 7. When processing images, a sensor
array is sampled (box 72) and the gray scale pixel
values (or other multi-scale values) from the array
are stored as a image (i.e., each pixel having a row
and column addsess)(box 74). The image gray
scale data is then processed as required for a
specific application (box 76). One such application
is described with reference to FIGs. 8-10.
FIG. 8 shows an illustrative method for identifying an individual on the basis of a handprint. This
application can be used, for example, to grant or
deny to an individual access to secure areas or to
computer terminals. The first step in the process,
shown in box 78, is to obtain successive array
samples, and to sum those samples to produce a
full image of a handprint. The processor typically
samples the sensing array at a rate such as 50 Hz,
making it desirable to sum the samples to provide
a reliable image.
The image then may be thresholded (box 80)
by finding the value of all non-zero pixels, and
subtracting a predetermined value (e.g., 0.3 times
the average pixel value) from each non-zero pixel.
Following the subtraction, thresholding continues
by setting any pixel having a value less than zero
to zero. This process eliminates noise, and permits
a person to hold a hand against the sensing array
for any period of time to facilitate clustering by the
processor.
The next step (box 82) is to convert the gray
scale handprint image to a binary image. All nonzero pixels are given a value of one. This gives
equal weight to each pixel, and provides a better
unit of measure for subsequent operations than that
available using gray scale centroid. FIG. 9 shows a
handprint image 106 resulting from this process.
The remaining steps of the method are described
with reference to FIGs. 9 and 10.

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whose centroid has an x coordinate of between 1.2 and 3.5 inches.
Next, handedness is determined. If the y coordinate of the thumb centroid is positive, the handprint image is of a left hand. If the y coordinate is
negative, it is the right hand
The clusters corresponding to the fingertips
then are identified and ordered (boxes 90 and 92).
To do this, the processor computes the distance
between centroid 108 and the centroid of each
cluster that has a centroid with a negative x coordinate (excluding the thumb). The processor adds to
this value the square of the x coordinate of the
centroid. The four centroids with the greatest values are the fingertips. The fingertips are then ordered according to their y coordinate values, in-

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cluding the thumb. If the handprint is of a left hand,
the thumb will have the greatest y coordinate, the
index finger the next highest, followed by the middie ring and little fingers. If it is a print of a right
hand, the ordering is reversed
As shown in box 94, the processor then locates
the furthest pixel from centroid 108 in each of

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fingertip clusters 114, 116, 118, 120, and 122.
Next, the center-bottom point 124 of the palm
of the hand is located (box 96). To do this, a new

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The next step (box 84 of FIG. 8) is to locate
the centroid 108 and the principle axes of binary
image 106. Centroid 108 is determined using the
centroid formulas described with respect to cluster-

ing above, where the value of all non-zero pixels
equals one. The X-axis 110 of a quadrant frame
with an origin at centroid 108 is parallel to the
principle axes corresponding to the lesser principle
moment, toward the heel of the palm. The Y-axis
112 is perpendicular to X-axis 110, completing a
right-handed coordinate frame. This identifies the
orientation of the hand.
The binary image is clustered into connected
regions (box 86), and the centroid of each connected region is determined. The cluster 114 corresponding to the tip of the thumb then is located
(box 88). Cluster 114 is the cluster having the
centroid which is furthest from X-axis 110, and

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coordinate frame, shown in FIG. 10, is defined. The
new coordinate frame is based at the same origin
as the original coordinate frame. The new X-axis
136 is defined to be parallel to a line connecting
the furthest pixel away from the centroid 126 of the
middle finger cluster 120 and the midpoint 128 of a
line segment drawn between the centroid 130 of
thumb cluster 114 to the centroid 132 of little finger
cluster 116. The new Y-axis 134 completes a righthanded coordinate frame. Using this coordinate
flame, the x coordinate of bottom-center point 124
is the x coordinate of the non-zero pixel with the
greatest x value in the new coordinate frame. The y
Coordinate is determined by finding the two nonzero pixels, with a x coordinate greater than zero,
that have the greatest and smallest y coordinates,
respectively (excluding pixels in thumb cluster
114). The average of these two y coordinates is the
y coordinate of center-bottom point 124.
The processor then determines the palm width
of the hand (box 98). The palm width is defined to
be the absolute distance between the two extreme
y values, excluding clusters identified as fingers.
The processor also determines the distances between the center-bottom of the hand 124 and the
furthest pixel of each fingertip (box 100).
A six-tuple is used to characterize an individual's handprint (see box 102). The six values that
form the six-tuple are the distances from bottomenter point 124 to the furthest pixel in each fingertip, and the palm width. This six-tuple can be
compared to a library of six-tuples which define a
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library of handprints (box 104). Thus, a handprint
from an unknown individual can be identified by
calculating the six-tuple defined as (di ,...,ds), and
comparing it to the six-tuples previously stored for
known individuals (defined as (cxi ,...,cxe ). A comparison is made by computing the euclidean distance between tuples for each known individual
according to the formula:

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D, - (1W,,i - d¡)2)1/2
i=1

is
The unknown handprint is identified as belonging to
the known individual with the lowest Dx value.
The flowcharts of FIGs. 11 and 12 illustrate
methods for implementing in processor 2 various
intelligent floor applications.
FIG. 11 flowcharts a method for recognizing
and controlling a motorized vehicle operating on a
surface (such as a floor) that is covered with sensor
arrays. The vehicle is identified and its position is
determined. The vehicle is then driven to a desired
location under feedback control. Collisions between
the vehicle and other objects are avoided using a
priority determining procedure.
The first step in controlling a motorized vehicle
is to sample the floor sensor array, as shown in
box 140. The process then identifies the vehicle by
its known footprint (box 142). To do this, the processor performs cluster analysis as described
above, determines the centroids of the detected
clusters and any distances between the centroids,
and compares this information to the known footprint of the vehicle. The processor then determines
the location of the vehicle on the floor (box 144),
and compares the location of the vehicle to the
desired location. The vehicle's previous location,
once available, can be used to limit the search for
the vehicle's current location. The motor and steering units of the vehicle are then actuated (as required for the type of vehicle being operated) to
drive the vehicle toward the desired location. The
processor repeatedly samples the sensing arrays
on the floor and adjusts the motor and steering
units (box 146) until the vehicle arrives at the
desired location.
The processor preferably provides a means for
avoiding collisions with obstacles, such as other
vehicles or people (see box 141). In one embodiment, if the vehicle comes within a predetermined
distance of another vehicle (or an object), the relative priorities of the two vehicles are determined
(box 143). The vehicle having the higher priority is
driven to the desired location (box 145). The lowerpriority vehicle remains stopped until the higher-

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priority vehicle has moved out of range (box 147),
and then continues toward the desired location.
Vehicles typically are given higher priority than
stationary objects, yet lower priority than people.
The direction and speed of the vehicle can be
modified as required to avoid obstacles and depending on traffic patterns on the floor.
FIG. 12 flowcharts a method for identifying an
individual on the basis of footprint analysis. The
first element of the footprint analysis is to sample
the array as shown in box 148. The footstep must
be sampled at a constant rate so that a template of
the footstep, comprising a series of footprint images, may be constructed. Once constructed, the
template describing the "unknown" (i.e., as yet
unidentified) footstep is compared to a library of
templates of "known" footsteps, so that the unknown footstep may be identified.
The processor computes the "origin" of the
ÍOotstep (box 150) preferably by defining the first
frame (the first footprint image of the footstep) as
the sensor array sample that detects the heel of
the footstep contacting the floor. The centroids of
this first footprint image and a second footprint
image are computed and averaged. This average
centroid defines the origin.
For each succeeding footprint image, until the
toe lifts off the floor at the end of the footstep, the
processor samples the sensing array, and computes and stores the centroid of the footprint image
(boxes 152, 154, and 156). The processor also
computes and stores the distance from the centroid
of each footprint image to the origin (box 158), and
the sum of all pixel values (box 160). The sum of
all pixel values is proportional to the weight applied

to the array. Once all footprint samples have been
taken (i.e., the foot no longer contacts the floor),
the processor reinterpolates the data (box 162).
If the processor took N samples (i.e., N footprint images) during a footstep, there will be N - 2
computed distances ad pixel sums (i.e., weights).
As shown in FIG. 13, this method focuses on the
relationship between distance versus weight. The
graph of FIG. 13 is derived from the weight versus
time and distance versus time information collected
through the series of array samples taken from the
time the heel of the foot contacts the sensor array
to the time the toe is lifted from the sensor. To
obtain data which is evenly spaced on the abscissa, the data is reinterpolated, preferably at intervals of 15/128 distance units. This results in 128
data points between 0 to 15 distance units (i.e.,
inches). (The number 15 is chosen here because
the largest expected footprint will not exceed 15
inches in length.) These 128 data points (some of
which may be zero) define a 128-tuple (di,...,d128 ,
which characterizes the unknown footstep (see box
164 of FIG. 12). The 128-tuple of the unknown

APLNDC00021799

13

EP 0 546 704 A2

footstep may be compared with the 128-tuple of
known footsteps ((Cxa,...,Cx128), for individual "x")
from a library of footsteps (box 166 of FIG. 12).
The footsteps may be compared using a Euclidean
distance measure:

128
x = (1 (di - Cx,¡)2)1/2
i=1

The unknown footstep (and the unknown individual
to whom the footstep belongs) is identified as the
footstep (and individual) having the smallest Dx

5

10

15

value.

Referring again to FIG. 4, details of illustrative
circuitry for implementing the intelligent work surfaces will now be described. Sensor arrays 12
preferably cover a work surface without significantly altering height or profile of the surface. Each
of sensor arrays 12 typically may be a piezoresistive tactile sensor array, such as a polymer ink
array. Sensor arrays 12 have separately addressable sensing elements, which typically comprise
intersections of rows and columns of conductive
elements. Thus, array 12 may be "sampled" by
sequentially addressing the columns and rows.
Sensor arrays suitable for use as array 12 are
commercially available from Interlink Electronics,
Carpinteria, California 93013. Of course, one skilled
in the art will appreciate that many other types of
sensors, such as variable capacitance sensors,
may be used to implement sensor array 12, without
departing from the scope or spirit of the invention.
Addressing circuitry 14 typically may include
circuitry for isolating each sensing element in array
12, to prevent undesirable current flow through
parallel paths in the array. Circuitry for implementing addressing circuitry 14 is described in commonly owned, co-pending, U.S. patent application
Serial No. 07/775,881, filed on October 11, 1991,
which is hereby incorporated by reference herein in
its entirety. A/D converter 16 may be implemented
using any commercially-available A/D converter circuit.
Addressing circuitry 14, A/D converter 16, and
buffer 18 are controlled via control lines 22. Control
signals are broadcast over lines 22 to all sensor
arrays 12 simultaneously, and data is sequenced
onto common data bus 20 via buffers 18. A strobe
signal times the conversion of the analog output
from sensor array 12 (through addressing circuitry
14) by A/D converter 16.
Any number of sensor arrays 12 (up to the
limits of the sensor select code) can be accessed
at the same rate as a single array, provided the
time required to select an array and output the data

20

25

30

35

40

45

50

55

14

from the array to bus 20 is less than the settling
period If more than 28 sensor arrays 12 are required, the data bus can be enlarged to accommodate additional sensors.
The primary parameters to be determined in an
intelligent work surface application are sensing element density and array sampling frequency. These
parameters are controlled largely by the application. For example, intelligent desktops generally
require greater sensing element density than intelligent floors.
Assuming a 32 microsecond settling period, an
800 nsec strobe (with data ready at the output 800
nsec after the strobe, as is typical of commercially
available A/D converters) and a 1 microsecond
addressing period, a sensing element of the array
can be addressed and sampled, on average, every
33.8 microseconds. Thus, a array of 16 x 16 sensors (each array having 256 sensing elements), can
generate data at a rate of 7.54 megapixels/second.
This data rate is similar to that of a standard 512 x
480 pixel video image, which generates 7.37
megapixels/second when updated at 30 Hz.
To implement typical modular input devices,
such as a keyboard or mouse, sensing element
densities of 0.125 to 0.25 in2 typically are adequate. At this resolution, an intelligent desktop generates data at rates from 1.2 to 4.9 megapixels/sec.
This is within an order of magnitude of video images at 30 Hz.
An area of 12' by 12' is typical for an office or
small common equipment area in an office building. In an area of this size, with sensing element
densities ranging from 1.5 in2 down to 0.25 in2
data can be generated at a rate of 0.27 Mpixels/sec
to 9.78 Mpixels/sec. In the midrange, using a sensor density of 3/4 in2, an intelligent floor generates
data at 1.10 Mpixels/sec, approximately fifteen percent of that generated by a single video camera.
However, these data rates can be altered substantially by increasing the sampling rate to 115 Hz, or
by decreasing the array resolution as described, for
example, in U.S. patent application Serial No.
07/775,881, discussed above.
It will be understood that the foregoing is merely illustrative of the principles of the invention, and
that various modifications can be made by those
skilled in the art without departing from the scope
and spirit of the invention. For example, the sensor
arrays of the present invention could be applied to
wall surfaces, and used interactively and in conjunction with projected information from a computer
display. An individual could respond to projected
information by contacting the "intelligent wall surface," to provide input to a computer. The scope of
this invention is limited only by the claims that
follow.

APLNDC00021800

15

EP 0 546 704 A2

multaneously a plurality of input devices on the
array, each of the plurality of input devices
comprising predetermined ones of the sensing
elements.

Claims
1. A work surface system comprising:
an array of sensing elements to form a
work surface, each sensing element of the
array producing a data output in response to
an input to the sensing element;
means for defining a first input device as
comprising a first plurality of sensing elements;
means for mapping each data output from
the first plurality of sensing elements to a
corresponding output of the first input device;
and
means for redefining the first input device
as comprising a second plurality of sensing
elements, wherein the means for mapping
maps data outputs from the second plurality of
sensing elements to a corresponding output of
the first input device.

5

10

is

20

2. The apparatus of claim 1 further comprising:
means for mapping the data outputs from
at least a portion of the first plurality of sensing
elements to a corresponding output of a second input device.
3.

4.

The apparatus of claim 1 further comprising:
means for defining a second input device
as comprising a third plurality of sensing elements; and
means for mapping each data output from
the third plurality of sensing elements to a
corresponding output of a second input device.

25

30

The apparatus of claim 1 further comprising
means for performing connected region analysis on the outputs from the first input device to
separate the outputs into connected regions.

35

5. The apparatus of claim 4 further comprising
means for determining the centroid of at least
one connected region.

40

6.

The apparatus of claim 1, wherein the first
input device is a keyboard interface.

9. The apparatus of claim 1, wherein the means
for defining comprises means for defining si-

10. A work surface system comprising:
a array of sensing elements to form a work
surface, each sensing element of the array
producing a data output in response to an
input to the sensing element;
means for defining a first input device as
comprising a first plurality of sensing elements;
means for mapping each data output from
the first plurality of sensing elements to a
corresponding output of the first input device;
and
means for mapping the data outputs from
at least a portion of first plurality of the sensing
elements to a corresponding output of a secOnd input device.
11. A method for using a sensor that has a plurality of sensing elements each of which produces a data output in response to an input,
comprising the steps of:
defining a first input device as comprising
a first plurality of the sensing elements;
mapping each data output from the first
plurality of the sensing elements to a corresponding output of the first input device; and
redefining the first input device as comprising a second plurality of the sensing elements, wherein the means for mapping maps
data outputs from the second plurality of the
S60Sing elements to a corresponding output of

the first input device.
12. The method of claim 11 further comprising:
mapping the data outputs from at least a
portion of the first plurality of the sensing elements to a corresponding output of a second
input device.

45

7. The apparatus of claim 1, wherein the first
input device is a mouse interface.
8. The apparatus of claim 1, wherein the first
input device comprises an image interface,
and wherein the apparatus further comprises
means for storing as an image a multi-level
representation the inputs to the first plurality of
sensing elements.

16

50

55

13. The method of claim 11 further comprising:
defining a second input device as comprising a third plurality of the sensing elements;
and
mapping each data output from the third
plurality of the sensing elements to a corresponding output of a second input device.
14. The method of claim 11, wherein the defining
step comprises the steps of:
sampling the sensing elements of the sensor;
determining whether a predetermined pattern of force has been applied to the sensor;
and
APLNDC00021801

17

EP 0 546 704 A2

defining the location and orientation of a
predetermined input device in response to the
predetermined pattern of force.
15. The method of claim 11, further comprising the
step of performing connected region analysis
on outputs from the first input device to separate the outputs into connected regions.

5

16. The method of claim 11, further comprising the
step of determining the centroid of at least one
connected region.

18

comparing the information characteristic of
the person with information characteristic of
known individuals; and
identifying the person as one of the known
individuals on the basis of the comparing step.

10

17. The method of claim 11, wherein the first input
device is a keyboard interface.

23. The method of claim 22, wherein the forceimage characteristic of the person comprises a
force-image of a handprint.

15

18. The method of claim 11, wherein the first input
device is a mouse interface.

19. The method of claim 18, further comprising the
steps of:
defining an origin to be the centroid of a
first force exerted within the defined region;
determining whether the centroid of a second force is spaced apart from the origin by at
least a first predetermined distance; and
generating signals indicative of moving a
cursor on a display screen in a predetermined
direction by a second predetermined distance
if the centroid of the second force is spaced
apart from the origin by at least said first
predetermined distance.
20. The method of claim 19, further comprising the
steps of signaling a click event upon detecting
a third force which exceeds a predetermined
value.

21. A method for using a sensor that has a plurality of sensing elements each of which produces a data output in response to an input,
comprising the steps of:
defining a first input device as comprising
a first plurality of the sensing elements;
mapping each data output from the first
plurality of the sensing elements to a corresponding output of the first input device; and
mapping the data outputs from at least a
portion of the first plurality of the sensing elements to a corresponding output of a second
input device.
22. A method for identifying a person, compnsing
the steps of:
sampling a tactile sensor array to record a
force-image that is characteristic of the person;
determining from the recorded force-image
information characteristic of the person;

20

25

30

35

40

24. The method of claim 23, wherein the sampling
step comprises:
summing pixels output from successive
samples of the sensor array to produce the
force-image;
subtracting a predetermined value from
each non-zero pixel;
setting to zero all pixels having a value
less than zero; and
setting to one all non-zero pixels.
25. The method of claim 23, wherein the determining step comprises:
defining an origin at a centroid of the
force-image;
determining a set of principle axes of the
force-image;
performing connected region analysis on
the force-image to to separate the force-image
into a plurality of connected regions;
identifying the connected regions corresponding to fingertips of the force-image;
identifying a pixel of each fingertip that is
spaced furthest from the origin;
calculating the distances between a predetermined point on the force-image and the
pixel of each fingertip that is spaced furthest
from the origin; and
calculating the width of the palm of the
force-image.
26. The method of claim 22, wherein the forceimage characteristic of the person comprises a
series of sequential force-images of a footprint.

45

50

55

27. The method of claim 22, wherein the determining step comprises:
defining an origin at a centroid of the first
force-image of the series of sequential forceimages;
calculating for each succeeding force-image: a centroid of the force-image, the distance between the centroid of the force-image
and the origin, and a sum of all pixel values of
the force-image; and
correlating for each force-image the sum
and the distance between he centroid of the
force-image and the origin, to characterize the
APLNDC00021802

19

EP 0 546 704 A2

28. The method of claim 27, further comprising the
step of reinterpolating the sum and the distance to obtain data values at predetermined
intervals for characterizing the person.

20

5

person.

10

15

20

25

30

35

40

45

50

55

APLNDC00021803

EP 0 546 704 A2

FIG. /
6

1

5

3

4

2

APLNDC00021804

EP 0 546 704 A2

FIG. 2
6

1

4

,

4

-

5'

5

,
3 3

2

APLNDC00021805

EP 0 546 704 A2

FIG. 3

1

Il
I
L

J

7/ 8

91

APLNDC00021806

EP 0 546 704 A2

FIG. 4

12

CONTROL SIGNALS

/ 22
,

ADDRESS CLOCKS
AND RESET
SENSOR
0

ROWS

COLUMNS

SENSOR
1

20
SENSOR
SELECT

STROBE

ASIC

DATA

A/D
CONVERTER
14

16

ROWS

COLUMNS

DATA BUS

18
DATA

A/D
CONVERTER

14

TRlSTATE
BUFEER

16

TRISTATE
BUFFER

18

12
SENSOR
n

ROWS

COLUMNS

/

14

, PATA

A/D ,
CONVERTER /

TRISTATE *
BUFFER i

16

18

APLNDC00021807

NO

>¢

36
32

FIG. 5
SAMPLE ARRAY,
FORM CLUSTERS,
COMPUTE CENTR010

42

o

30
I

CLUSTERS
YES
HRE
CLUSTERS

34

ONE
CLUSTER
?
YES

YES

NO

IS A
KilOill IICOUlf INIED

AOCT

YES
ADD MODULE AND ITS
POSITION AND ORIENTATION
TO 'ACTIVE" LIST

40

IC
DEVICE IS IT

01

YES OPTIONAL PROCESSING
FOR CONTACT GUTSIDE
0E ACTIVE REGIONS

44

38
-

y OPTIONAL PROCESSING
TO ACT ON MULTIPLE CONTACTS

à;

QUT
0 CG 0
NO

NO

46
APPROPRIATE PROCESSING

FOR THE DEVICE

APLNDC00021808

EP 0 546 704 A2

FIG. 6
DEFINE
MOUSE
ACTIVE
REGION

,50

54
52
LUSTER
NO
RESET RUNNING
IN MOUSE REGION
TOTAL(X,Y)
9
COUNTERS
YES
56
3
YES
ORIGIN ESTABLISHED
NO
58
ADO CENTROID X,Y ~
VALUES TO A
RUNNING TOTAL;
DECREMENT COUNTER

TAKE NEXT
I SAMPLE

64
IS
SUM OF
PIXEL VALUES IN
CLUSTER > CLICK
THRESHOLD
?
YES

68

NO
IS
CENTROID >'ORIGIN
061ANCE FROM ORIGI
I
YES

NO

70

SIGNAL A
CLICK EYENT ~66

MOVE CURSOR
TO NEW POSITION

60

HAVE

WE SAMPLED
A PREDETERMINED

NO

NUMBER OF
TIMES

TAKE NEXT

,

SAMPLE

YES

MARK ORIGIN;
FIND AVERAGE
CENTROID

62

APLNDC00021809

EP 0 546 704 A2

FIG. 7
SAMPLE
THE
ARRAY

,72
¡

STORE THE
GRAY SCALE PIXEL
VALUES AS AN IMAGE
PROCESS
AS
REQUIRED

74

\ 76
~

FIG. i 3

WEIGHT

DISTANCE

APLNDC00021810

EP 0 546 704 A2

FIG. 8
78

SUM SUCCESSIVE ARRAY SAMPLES TO OBTAIN HAND IMAGE
THRESHOLD THE IMAGE

SET ALL NON-ZERO PIXELS TO ONE

80
82
84

LOCATE THE CENTROID AND PRINCIPLE AXES OF THE BINARY IMAGE
FORM CLUSTERS OF CONNECTED REGIONS

86

LOCATE CLUSTER CORRESPONDING TO THE THUMB
LOCATE CLUSTERS CORRESPONDING TO THE FINGERTIPS

90

ORDER THE FINGERTIPS

92

FIND EACH FINGERTIP PIXEL FURTHEST FROM ORIGIN

94

i

DEFINE NEW COORDINATE FRAME:
FIND THE CENTER-BOTTOM POINT OF THE HAND
FIND THE PALM WIDTH 0E THE HAND

96
98

DETERMINE DISTANCES BETWEEN FURTHEST PIXEL
OF EACH FINGERTIP AND CENTER-BOTIDM

100

DEFINE A SIX-TUPLE OF KNOWN VALUES

102

COMPARE SlX-TUPLE OF HAND IMAGE WITH SlX-TUPLE
OF HAND IMAGES FROM LlBRARY OF HAND IMAGES

104

TO IDENTIFY SAMPLED IMAGE
APLNDC00021811

EP 0 546 704 A2

FIG. 9
106
-

120

118

122

116

114

108 112
Y-AXIS
110
X-AXIS

APLNDC00021812

EP 0 546 704 A2

FIG. 10
106
118

126

120

122

116
132
128

0

108

114
134

NEW
Y-AXIS

130

136
NEW
X-AXIS
124

APLNDC00021813

EP 0 546 704 A2

FIG. 11

SAMPLE
FLOOR SENSOR
ARRAY
IDENTIFY VEHICLE
BY KNOWN FOOTPRINT
DETERMINE
VEHICLE LOCATION
IS
141
VEHICLE WITHIN
PREDETERMINED DISTANCE OF
ANOTHER VEHICLE
OR OBJECT

146
|
DRIVE VEHICLE'S MOTOR
AND STEERING UNITS
TOWARD DESIRED LOCATION

,140

,142

~

144
143

YES

DETERMINE
RELATIVE PRIORITY

NO

YES

145

IS THE
HICLE HIGHΠPRIOWY
?
NO 147
STOP UNTIL OTHER
IS OUT OF RANGE

APLNDC00021814

EPO546704A2

SAMPLE THE ARRAY

,148

COMPUTE THE "ORIGIN° 0E THE FOOTPRINT

t

SAMPLE THE ARRAY

150

152

is
1 4
THE FOOT
NO
STILL IN CONTACT
WH ARRAY

YES

COMPUTE AND STORE THE CENTROID
156
OF THE FOOTPRINT
"
COMPUTE AND STORE DISTANCE FROM , ,158
CENTROID TO ORIGIN

COMPUTE AND STORE SUM 160
0E ALL PIXEL VALUES ~'
REINTERPOLATE DATA

DEFINE A 128-TUPLE
OF KNOWN VALUES

162

-"

164

t

COMPARE 128-TUPLE OF FOOTPRINT
IMAGE WITH 128-TUPLE OF FOOTPRINT
IMAGES FROM LIBRARY TO IDENTIEY
166'
THE SAMPLED IMAGE

APLNDC00021815