WO1990008366A1 - Biometrics - Google Patents

Biometrics Download PDF

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Publication number
WO1990008366A1
WO1990008366A1 PCT/GB1990/000066 GB9000066W WO9008366A1 WO 1990008366 A1 WO1990008366 A1 WO 1990008366A1 GB 9000066 W GB9000066 W GB 9000066W WO 9008366 A1 WO9008366 A1 WO 9008366A1
Authority
WO
WIPO (PCT)
Prior art keywords
identification
individuals
measuring
incorporates
finger
Prior art date
Application number
PCT/GB1990/000066
Other languages
French (fr)
Inventor
David Oswald Clayden
Roger Cullis
Original Assignee
National Research Development Corporation
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by National Research Development Corporation filed Critical National Research Development Corporation
Publication of WO1990008366A1 publication Critical patent/WO1990008366A1/en

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Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/117Identification of persons
    • A61B5/1171Identification of persons based on the shapes or appearances of their bodies or parts thereof
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/107Static hand or arm
    • G06V40/11Hand-related biometrics; Hand pose recognition
    • GPHYSICS
    • G07CHECKING-DEVICES
    • G07CTIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C9/00Individual registration on entry or exit
    • G07C9/20Individual registration on entry or exit involving the use of a pass
    • G07C9/22Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder
    • G07C9/25Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder using biometric data, e.g. fingerprints, iris scans or voice recognition
    • G07C9/257Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder using biometric data, e.g. fingerprints, iris scans or voice recognition electronically

Definitions

  • BIOMETRICS This invention relates to biometrics and, in particular, to measurements used for the identification of individuals. With any measurement that is to be used for identification purposes it is essential to estimate the accuracy and the repeatability of the measurement. In the case of measurements on human parts it is necessary to allow tolerances because of variations of temperature, humidity, diet, etc., over the time interval between the instant at which the measurement was made and that at which the reference measurement was made. It is pointless measuring something to an accuracy of microns if variations in the measurement amount to millimetres. Secondly an appreciation of the laws of statistics is essential. Almost any measurements of any human parts are most likely to be statistically normally distributed.
  • the average length of the middle finger of adults is about 85mm, with a probable deviation from 75 to 95mm. If measurements are quantised Into, for instance, one millimetre units then one measurement would divide the total population into 20 very unequal categories, with a large proportion of the population having a finger length close to the average. Of course the lengths of the other fingers can be measured but here the second law of statistics applies, that is that alternative measurements are likely to be correlated with the first measurement. In this case the relative lengths of the fingers are likely to be close to standard proportions, so that it is only the departures from these standard proportions which are of value. If these departures are small compared with the tolerances, then the measurements are of little significant value.
  • the hand is used as the medium for biometric measurements because it 1s readily inserted into a measuring device and it possesses a number of parameters which are easily measured but are substantially Independent of one another.
  • apparatus for the identification of Individuals comprising a plurality of measuring means for measuring a corresponding plurality of biometric parameters of an individual, comparator means for comparing the outputs from said measuring means with sets of stored values and combining means for combining the outputs of said comparator means to produce either an acceptance or a rejection signal dependent on the combined results of comparisons made by said comparator means.
  • the apparatus preferably includes measuring means for measuring at least two substantially independent biometric parameters.
  • the apparatus may also includes measuring means for measuring at least two partially correlated biometric parameters.
  • Figure 1 shows a side elevation of a clenched fist with protuberances due to the underlying bone structure
  • Figure 2 shows a corresponding plan view of the fist
  • Figure 3 shows the bone structure of the fist of Figure 2
  • Figures 4 a to c show in plan and section a finger nail with extrusion ridges thereon
  • Figure 5 shows the underside of a pair of hands with the major creases which are visible on the surface of the skin
  • Figure 6 shows a hand playing a keyboard
  • Figure 7 is a schematic drawing of an apparatus used for biometric measurements for purposes of identification; and Figure 8 is a graph showing the effect of tolerance settings on customer rejection rates;
  • Figure 9 is a schematic drawing of apparatus suitable for credit card verification.
  • an analysis of the topography of the knuckles is a useful basis for person identification.
  • knuckles appear to be a complicated three dimensional pattern of a skin surface, the problem of recognition is similar to the problem of recognising human faces, but without the problem of variable hairy excrescences or spectacles.
  • the relative position of the main veins is likely to conform to a normal distribution because they are constrained by the bone structure of the knuckles and the wrist. However the positions of the minor veins and junctions are unconstrained.
  • the palm ( Figure 5) also has features which may be utilised. Specifically, the pattern of creases 50-55 on the palm is particularly useful because it is not correlated with size and because the pattern of the left hand is not necessarily identical with that of the right hand.
  • the creases 56-58 corresponding to the finger joints are gross features which are readily susceptible to optical measurement. Their relative positions from finger to finger provide a quantisable indication of identity, whilst their absolute spacings are correlated with the lengths of the metacarpals. This latter therefore provides for a check that the same hand is being measured when the measuring position has been changed.
  • Musicians who play instruments with a keyboard develop remarkable skills with their fingers. They are capable of learning phrases which their fingers can play very fast, quite accurately, and with very consistent timing. Typists develop similar skills. The proportion of the population who have finger skills 1s increasing at a considerable rate as computers become accessible to more people. Finger dexterity is therefore a further parameter which may be used for purposes of identification.
  • a MIDI (musical Instrument digital interface) keyboard 60 ( Figure 6) would be appropriate as this is capable of encoding duration and velocity characteristics of a sequence of key presses.
  • Each candidate would choose and learn to play a phrase of between ten and twenty 'notes', concentrating on accuracy and constancy of timing.
  • This phrase is used as a 'silent keyboard signature' to provide access to services.
  • the probability of an intruder being able to produce the same 'signature' 1s very small. Because of this, it is probable that, for a restricted population such as the users of a computer installation, such a test could be used not only to confirm identity but also to declare identity.
  • a biometric parameter is measured by an input device 71. After analysis 1n a signal analyser 72, the output from a signal processor 73 is stored in a look-up store 74. In subsequent live use, the values from the signal analyser 72 and the look-up store 74 are fed to a comparator 75 which controls a gating device 76 which control subsequent processing of the application.
  • the tolerance setting of the gating device is adjusted to give the desired acceptance rate ( Figure 8).
  • an Input device 91 scans a number of biometric parameters and passes the outputs to a signal processor 92 and subsequently to comparator circuits 93.
  • Reference parameters are stored on an identity card 94 which is fed into a card reader 95.
  • Data extracted by a management system 96 is fed via a signal processor 97 to the comparators 93.
  • the comparators produce normalised output signals dependent on the difference between the input si-gnals and the reference signals. These output signals are then fed to an adder 98 which produces a control signal for the pass/reject decision.
  • the stored reference may be continuously updated by the most recent measurements so that it constitutes a moving average. This will take account of long term changes in the biometric parameters used as a basis of the test.

Abstract

Apparatus for the identification of individuals comprises a plurality of measuring means for measuring a corresponding plurality of biometric parameters of an individual, a comparator or comparators for comparing the outputs from the measuring means with sets of stored values and combining means for combining the outputs of the comparator means to produce either an acceptance or a rejection signal dependent on the combined results of comparisons made by the comparator.

Description

BIOMETRICS This invention relates to biometrics and, in particular, to measurements used for the identification of individuals. With any measurement that is to be used for identification purposes it is essential to estimate the accuracy and the repeatability of the measurement. In the case of measurements on human parts it is necessary to allow tolerances because of variations of temperature, humidity, diet, etc., over the time interval between the instant at which the measurement was made and that at which the reference measurement was made. It is pointless measuring something to an accuracy of microns if variations in the measurement amount to millimetres. Secondly an appreciation of the laws of statistics is essential. Almost any measurements of any human parts are most likely to be statistically normally distributed. The consequence of this is that many more people produce measurements which are closer to the average than those which are unusual, making it easier for an intruder who has average measurements to masquerade successfully. This makes it particularly difficult to devise any biometric identification scheme which will cope with average human beings. Another law of statistics indicates that additional measurements are most probably related to a first measurement so that they have less information value than the first measurement.
There already exist devices which measure the lengths of the fingers of one hand, either by mechanically feeling or by optically scanning. The measurements are then compared with corresponding values stored either In a master file or in a chip card and a decision is made either to accept or reject the candidate or culprit depending on the closeness of the measurements to the registered values.
The principle behind this method is that, after growing through childhood, the dimensions of bones remain constant for many years. If we could really make contact with the bones of the hand we could measure their dimensions with an accuracy of a few micrometres, and be able to consistently repeat such measurements over intervals of years. Such measurements could form a sound basis for identity verification. Unfortunately the bones are covered with soft tissue which 1s elastic and not constant in dimensions so that any measurement made through the skin can be subject to a substantial margin of error and lack of repeatability. Accurate measurements could probably be made using X-rays, but this is unlikely to be acceptable as a general purpose identification scheme.
Existing devices take measurements of the hand while it is spread on a flat surface, so that measurements suffer from the inconsistencies of the web between the fingers and the variations in length of the finger nails. These inconsistencies probably amount to about plus or minus one millimetre, so 1t is pointless to try to make measurements with units much smaller than a millimetre.
The average length of the middle finger of adults is about 85mm, with a probable deviation from 75 to 95mm. If measurements are quantised Into, for instance, one millimetre units then one measurement would divide the total population into 20 very unequal categories, with a large proportion of the population having a finger length close to the average. Of course the lengths of the other fingers can be measured but here the second law of statistics applies, that is that alternative measurements are likely to be correlated with the first measurement. In this case the relative lengths of the fingers are likely to be close to standard proportions, so that it is only the departures from these standard proportions which are of value. If these departures are small compared with the tolerances, then the measurements are of little significant value.
In our British patent No.2156127B there 1s described a means of identifying individuals by scanning the subcutaneous vein structure and comparing it with a set of previously input stored values.
Whilst this provides a satisfactory method for identification, In order to avoid ambiguity and either false acceptances or false rejections, it is necessary either to make repeated scans or to make measurements at a very high resolution. On occasion, this 1s not feasible. We have therefore devised more rapid techniques based on making a plurality of measurements and combining the results. This technique gives a high acceptance/rejection accuracy with a much higher speed of measurement.
Preferably, the hand is used as the medium for biometric measurements because it 1s readily inserted into a measuring device and it possesses a number of parameters which are easily measured but are substantially Independent of one another. According to the present invention there is provided apparatus for the identification of Individuals comprising a plurality of measuring means for measuring a corresponding plurality of biometric parameters of an individual, comparator means for comparing the outputs from said measuring means with sets of stored values and combining means for combining the outputs of said comparator means to produce either an acceptance or a rejection signal dependent on the combined results of comparisons made by said comparator means.
The apparatus preferably includes measuring means for measuring at least two substantially independent biometric parameters.
The apparatus may also includes measuring means for measuring at least two partially correlated biometric parameters. The invention will now be described with reference to the accompanying drawings, in which:
Figure 1 shows a side elevation of a clenched fist with protuberances due to the underlying bone structure; Figure 2 shows a corresponding plan view of the fist; Figure 3 shows the bone structure of the fist of Figure 2; Figures 4 a to c show in plan and section a finger nail with extrusion ridges thereon; Figure 5 shows the underside of a pair of hands with the major creases which are visible on the surface of the skin; Figure 6 shows a hand playing a keyboard;
Figure 7 is a schematic drawing of an apparatus used for biometric measurements for purposes of identification; and Figure 8 is a graph showing the effect of tolerance settings on customer rejection rates;
Figure 9 is a schematic drawing of apparatus suitable for credit card verification. We have found that an analysis of the topography of the knuckles is a useful basis for person identification. Insofar as knuckles appear to be a complicated three dimensional pattern of a skin surface, the problem of recognition is similar to the problem of recognising human faces, but without the problem of variable hairy excrescences or spectacles.
Referring now to Figures 1 to 3 of the drawings, more accurate and more consistent measurements of bone lengths can be achieved by taking measurements of the clenched fist, locating the back of the hand 1 against a reference surface 2 and measuring the distances L1-L4 of the end of the etacarpals 3-6 from the styloid process 7 of the ulna with an optical gauge 8. In this way the thickness of the tissue is reduced to a minimum and measurements with a consistency down to a tenth of a millimetre are possible. Such an improvement in accuracy much improves the ability to discriminate against intruders.
It is always important to estimate the probability that an intruder having average measurements will be successful. Machines designed for identity verification are fitted with an adjustment to control the threshold between false acceptance and false rejection. If this 1s adjusted so that the number of false rejections is small, there is a temptation to believe that the machine is working well, whereas the machine is more Hkely to accept an intruder.
There is a need to find measurements of a number of different kinds, so that they are related to each other as little as possible. If measurements are normally distributed, there is also a need to assign a low weighting on those measurements which are close to the average.
With vein patterns, first the problems of reliably locating the blood vessels must be overcome. Optical, infra-red and far infra-red wavelengths are in use for diagnostic purposes in the medical field. Each of these technologies has Its advantages and limitations. Far Infra-red waves penetrate deeper but give correspondingly less resolution. At optical wavelengths, colour filters can be used to provide more detailed information, but only of the surface. To achieve good thermal images it is standard practice to allow time for the temperature distribution of the patient to normalise before the thermal scan. This implies that there are problems with thermal time constants, particularly when the patient has been subjected to extremes of temperature. It 1s known that the body automatically modifies the flow of blood to the arms and legs in order to maintain the temperature of the central part of the body within close limits, with the result that the hands and feet can become very cold in cold weather. It is also known that scratches and inflammation on the back of the hand result in local hot areas, thus confusing the thermal image.
When the blood vessel pattern has been captured, several techniques are available to analyse the pattern Into features such as junctions, parallel lines, s-bends etc. One powerful method for this is two-dimensional auto-correlation. The pattern can then be described in terms of the distances between, and the orientation of, such features. This description is then compared with the stored description and a decision made on the basis of a closeness of fit.
The relative position of the main veins is likely to conform to a normal distribution because they are constrained by the bone structure of the knuckles and the wrist. However the positions of the minor veins and junctions are unconstrained.
Other parameters are of value for identification. One of these is the extrusion pattern of the finger nails (Figures 4a-£>. This comprises a series of furrows 40 and ridges 41 which are scanned with a laser diode radiation source 42 and an optical detector 43. The signature of this parameter changes slowly with time as the individual ages or suffers accidents such as a blow to the growth point of the nail. It is therefore desirable to use measured values to update the stored reference, which thus becomes a moving average.
The palm (Figure 5) also has features which may be utilised. Specifically, the pattern of creases 50-55 on the palm is particularly useful because it is not correlated with size and because the pattern of the left hand is not necessarily identical with that of the right hand.
The creases 56-58 corresponding to the finger joints are gross features which are readily susceptible to optical measurement. Their relative positions from finger to finger provide a quantisable indication of identity, whilst their absolute spacings are correlated with the lengths of the metacarpals. This latter therefore provides for a check that the same hand is being measured when the measuring position has been changed. Musicians who play instruments with a keyboard develop remarkable skills with their fingers. They are capable of learning phrases which their fingers can play very fast, quite accurately, and with very consistent timing. Typists develop similar skills. The proportion of the population who have finger skills 1s increasing at a considerable rate as computers become accessible to more people. Finger dexterity is therefore a further parameter which may be used for purposes of identification. For this purpose, a MIDI (musical Instrument digital interface) keyboard 60 (Figure 6) would be appropriate as this is capable of encoding duration and velocity characteristics of a sequence of key presses. Each candidate would choose and learn to play a phrase of between ten and twenty 'notes', concentrating on accuracy and constancy of timing. This phrase is used as a 'silent keyboard signature' to provide access to services. The probability of an intruder being able to produce the same 'signature' 1s very small. Because of this, it is probable that, for a restricted population such as the users of a computer installation, such a test could be used not only to confirm identity but also to declare identity. It can be implemented cheaply on a personal computer with the requisite MIDI interface, and requires a program which not only checks that keys are pressed in the correct sequence but also at the correct time intervals, within close tolerances. Referring now to Figure 6, in use a biometric parameter is measured by an input device 71. After analysis 1n a signal analyser 72, the output from a signal processor 73 is stored in a look-up store 74. In subsequent live use, the values from the signal analyser 72 and the look-up store 74 are fed to a comparator 75 which controls a gating device 76 which control subsequent processing of the application.
The tolerance setting of the gating device is adjusted to give the desired acceptance rate (Figure 8).
In a practical application, an Input device 91 scans a number of biometric parameters and passes the outputs to a signal processor 92 and subsequently to comparator circuits 93. Reference parameters are stored on an identity card 94 which is fed into a card reader 95. Data extracted by a management system 96 is fed via a signal processor 97 to the comparators 93. The comparators produce normalised output signals dependent on the difference between the input si-gnals and the reference signals. These output signals are then fed to an adder 98 which produces a control signal for the pass/reject decision.
Conveniently the stored reference may be continuously updated by the most recent measurements so that it constitutes a moving average. This will take account of long term changes in the biometric parameters used as a basis of the test.

Claims

1. Apparatus for the Identification of individuals characterled in that it comprises a plurality of measuring means for measuring a corresponding plurality of biometric parameters of
5 an individual, comparator means for comparing the outputs from said measuring means with sets of stored values and combining means for combining the outputs of said comparator means to produce either an acceptance or a rejection signal dependent on the combined results of comparisons made by said comparator 10 means.
2. Apparatus for the identification of individuals as claimed in claim 1 characterised in that it includes measuring means for measuring at least two said biometric parameters.
3. Apparatus for the identification of individuals as claimed in 15 claim 2 characterised in that it includes means for measuring the topography of the knuckles.
4. Apparatus for the identification of individuals as claimed in claim 3 characterised in that it includes means for taking measurements of the clenched fist.
205. Apparatus for the identification of individuals as claimed 1n claim 4 characterised 1n that it includes means for locating the back of the hand against a reference surface and means for measuring the distances of the end of the metacarpals from the styloid process of the ulna.
25 6. Apparatus for the Identification of individuals as claimed in any one of the preceding claims characterised in that 1t incorporates means for measuring the positions of minor veins and junctions.
7. Apparatus for the identification of individuals as claimed in 0 any one of the preceding claims characterised 1n that it incorporates means for measuring the extrusion pattern of a finger nail .
8. Apparatus for the identification of individuals as claimed in any one of the preceding claims characterised 1n that it 5 incorporates means for measuring the pattern of creases on the palm.
9. Apparatus for the Identification of individuals as claimed in claim 8 characterised in that it incorporates means for comparing the pattern of creases on the left palm with that on the right palm.
10. Apparatus for the identification of individuals as claimed in claim 8 characterised in that it incorporates means for locating the creases corresponding to the finger joints.
11. Apparatus for the Identification of Individuals as claimed in claim 10 characterised in that 1t incorporates means for measuring the relative positions from finger to finger of the creases corresponding to the finger joints.
12. Apparatus for the identification of individuals as claimed in claim 10 characterised in that it incorporates means for measuring the absolute spacings of the creases corresponding to the finger joints.
13. Apparatus for the identification of individuals as claimed in any one of the preceding claims characterised in that 1t incorporates keyboard means responsive to the incidence and duration of imposed key strokes.
PCT/GB1990/000066 1989-01-16 1990-01-16 Biometrics WO1990008366A1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GB8900866.8 1989-01-16
GB898900866A GB8900866D0 (en) 1989-01-16 1989-01-16 Biometrics

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GB (2) GB8900866D0 (en)
WO (1) WO1990008366A1 (en)

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1995026013A1 (en) * 1994-03-24 1995-09-28 Minnesota Mining And Manufacturing Company Biometric, personal authentication system
US5594806A (en) * 1994-06-20 1997-01-14 Personnel Identification & Entry Access Control, Inc. Knuckle profile indentity verification system
US5892838A (en) * 1996-06-11 1999-04-06 Minnesota Mining And Manufacturing Company Biometric recognition using a classification neural network
US8670596B2 (en) 2000-09-06 2014-03-11 Hitachi, Ltd. Personal identification device and method
WO2017195211A1 (en) 2016-05-11 2017-11-16 Sambit Sahoo Biometric unique combination identification system
US10621318B1 (en) * 2016-10-05 2020-04-14 Lawrence F. Glaser Operating systems, software, applications (apps) and services for receiving, processing and storing a plurality of commands bearing biometric inputs
WO2021156746A1 (en) * 2020-02-03 2021-08-12 Global Id Sa A method, a system and a biometric server for controlling access of users to desktops in an organization

Families Citing this family (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB2243934A (en) * 1990-05-09 1991-11-13 Shorrock Ltd Access control
US5335288A (en) * 1992-02-10 1994-08-02 Faulkner Keith W Apparatus and method for biometric identification
US5793881A (en) * 1995-08-31 1998-08-11 Stiver; John A. Identification system
IL122230A (en) * 1997-11-17 2003-12-10 Milsys Ltd Biometric system and techniques suitable therefor
GB2332969A (en) * 1998-01-06 1999-07-07 Torche Clinical Consultancy Lt Measuring physiological data and identifying persons
WO2001009845A1 (en) * 1999-08-03 2001-02-08 Siemens Aktiengesellschaft Biometric recognition method
US20020049714A1 (en) 2000-05-11 2002-04-25 Shunpei Yamazaki Communication system
JP4704129B2 (en) 2005-06-30 2011-06-15 富士通株式会社 Biometric authentication method, biometric authentication apparatus, and blood vessel image reading apparatus
JP4492705B2 (en) * 2008-01-21 2010-06-30 株式会社日立製作所 Biometric identification device
JP2012128868A (en) * 2012-02-16 2012-07-05 Hitachi Ltd Feature image photographing device and personal identification device

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4032889A (en) * 1976-05-21 1977-06-28 International Business Machines Corporation Palm print identification
GB2171828A (en) * 1985-03-01 1986-09-03 Mitsubishi Electric Corp An individual recognition system
CH661428A5 (en) * 1984-11-08 1987-07-31 Edouard Menoud Method for identifying a person from the geometry of his hand
WO1988004153A1 (en) * 1986-12-02 1988-06-16 Kodak Limited Information concerned with the body of an individual

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB1304555A (en) * 1969-11-20 1973-01-24
BE790510A (en) * 1971-11-04 1973-02-15 Rothfjell Rolf E METHOD FOR THE IDENTIFICATION OF PERSONS USING SELECTED CHARACTERISTIC CURVES OF THE BODY
DE2845567A1 (en) * 1978-10-19 1980-04-30 Siemens Ag PERSONAL ID CARD
US4449189A (en) * 1981-11-20 1984-05-15 Siemens Corporation Personal access control system using speech and face recognition
ATE30973T1 (en) * 1982-02-15 1987-12-15 Holoplex Systems Ltd HOLOGRAM VIEWING DEVICE; UNIFIED DEVICE FOR DIRECT VIEWING OF HOLOGRAMS; ITEM USED FOR MAKING HOLOGRAMS.
NL8303649A (en) * 1983-10-24 1985-05-17 Philips Nv METHOD FOR DETERMINING THE USE OF A USER OF A SUBSCRIBER FOR SIGNAL TRANSMISSION.
GB8509001D0 (en) * 1985-04-09 1985-05-15 Strain J Optical data storage card

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4032889A (en) * 1976-05-21 1977-06-28 International Business Machines Corporation Palm print identification
CH661428A5 (en) * 1984-11-08 1987-07-31 Edouard Menoud Method for identifying a person from the geometry of his hand
GB2171828A (en) * 1985-03-01 1986-09-03 Mitsubishi Electric Corp An individual recognition system
WO1988004153A1 (en) * 1986-12-02 1988-06-16 Kodak Limited Information concerned with the body of an individual

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
IBM Technical Disclosure Bulletin. Vol. 17, No. 11, April 1975, New York US page 3346 SPILLANE: "Keyboard Apparatus for Personal Identification" *
IBM TECHNICAL DISCLOSURE BULLETIN. vol. 17, no. 11, April 1975, NEW YORK US page 3346 SPILLANE: "keyboard apparatus for personal identification" see page 3346 *
IBM TECHNICAL DISCLOSURE BULLETIN. vol. 21, no. 6, November 1978, NEW YORK US pages 2523 - 2525; NASSIMBENE: "personal verification - knuckle contour detection" see page 2523, line 1 - page 2525, line 59; figures *
PROCEEDINGS OF 1976 CARNAHAN CONFERENCE ON CRIME COUNTERMEASURES; MAY 1976; LEXINGTON, USA; pages 23 - 30; HABERMAN e.a.: "Automatic identification of personnel through speaker and signature verification - system descryption and testing" *
PROCEEDINGS OF 1981 CARNAHAN CONFERENCE ON CRIME COUNTERMEASURES; 13 - 15 MAY 1981; LEXINGTON, USA; PAGES 77 -82; WOODARD e.a.: "Automated entry control: RADC technology development results and future plans" see page 79, column 2, line 42, - page 81, column 2, line 70; figures *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1995026013A1 (en) * 1994-03-24 1995-09-28 Minnesota Mining And Manufacturing Company Biometric, personal authentication system
US5719950A (en) * 1994-03-24 1998-02-17 Minnesota Mining And Manufacturing Company Biometric, personal authentication system
US5594806A (en) * 1994-06-20 1997-01-14 Personnel Identification & Entry Access Control, Inc. Knuckle profile indentity verification system
US5892838A (en) * 1996-06-11 1999-04-06 Minnesota Mining And Manufacturing Company Biometric recognition using a classification neural network
US8670596B2 (en) 2000-09-06 2014-03-11 Hitachi, Ltd. Personal identification device and method
WO2017195211A1 (en) 2016-05-11 2017-11-16 Sambit Sahoo Biometric unique combination identification system
US10621318B1 (en) * 2016-10-05 2020-04-14 Lawrence F. Glaser Operating systems, software, applications (apps) and services for receiving, processing and storing a plurality of commands bearing biometric inputs
WO2021156746A1 (en) * 2020-02-03 2021-08-12 Global Id Sa A method, a system and a biometric server for controlling access of users to desktops in an organization

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JPH04502717A (en) 1992-05-21
GB8900866D0 (en) 1989-03-08
EP0454750A1 (en) 1991-11-06
GB9000895D0 (en) 1990-03-14
GB2229844A (en) 1990-10-03

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