EP0333826A1 - Procede et appareil d'analyse d'empreintes digitales - Google Patents

Procede et appareil d'analyse d'empreintes digitales

Info

Publication number
EP0333826A1
EP0333826A1 EP88908740A EP88908740A EP0333826A1 EP 0333826 A1 EP0333826 A1 EP 0333826A1 EP 88908740 A EP88908740 A EP 88908740A EP 88908740 A EP88908740 A EP 88908740A EP 0333826 A1 EP0333826 A1 EP 0333826A1
Authority
EP
European Patent Office
Prior art keywords
image
section
distance
fingerprint
values
Prior art date
Legal status (The legal status 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 status listed.)
Withdrawn
Application number
EP88908740A
Other languages
German (de)
English (en)
Inventor
Richard 24 High Street Wheatley
Davis 93 North Street Jansons
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
IMAGEPACK Ltd
Original Assignee
IMAGEPACK Ltd
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 IMAGEPACK Ltd filed Critical IMAGEPACK Ltd
Publication of EP0333826A1 publication Critical patent/EP0333826A1/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME 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
    • G07C9/00—Individual registration on entry or exit
    • G07C9/20—Individual registration on entry or exit involving the use of a pass
    • G07C9/22—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder
    • G07C9/25—Individual 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
    • G07C9/257—Individual 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/12—Fingerprints or palmprints
    • G06V40/1347—Preprocessing; Feature extraction

Definitions

  • This invention relates to fingerprint analysis and is applicable to identity verification, and more especially, but not necessarily, concerns apparatus and methods for encoding and storing information relating to fingerprints and for verifying the identity of a person.
  • information is obtained from a fingerprint by deriving data from an area of the fingerprint, that data relating to the number of ridges counted in a direction orthogonal to a line across the area, the count being obtained at each of a plurality of positions along the line.
  • the data is derived by thresholding a grey level image of the fingerprint.
  • a measure of ridge count by measuring the distance between two ridges (or troughs). Only a small section of a fingerprint containing, say, two or three ridges can give such a measurement, the inverse of which relates directly to the number of ridges per unit distance in that section. Clearly, with only two or three ridges in a section, an integral count of ridges would not give a characteristic value. Moreover, by making such a measurement on a small section of a fingerprint, the measurement can be repeated for a plurality of other such sections, thus to give a relatively large set of characteristic values which together assist in more uniquely identifying the fingerprint.
  • the sections analysed are arranged in "rows” and "columns”. Additional characterising values can be provided by obtaining values for ridge count along each of plurality of lines extending across the fingerprint image, again obtaining the count by measuring ridge spacing.
  • apparatus for deriving characteristic data from a fingerprint comprising means for receiving a representation of an area of an image of the fingerprint and means arranged to scan a section of the area, in a given direction, to compare bit patterns of distinct portions of the section following one another in said direction with neighbouring bit patterns, thereby to obtain a series of values corresponding to the distances scanned from each distinct portion to that neighbouring bit pattern having maximum correlation with the distinct portion.
  • a plurality of characteristic values can be obtained by splitting the image into a two- dimensional array of rows and columns of such sections and by obtaining a value for each such section, the sections selected for analysis not all being in the same column or row.
  • apparatus for deriving characteristic data from a fingerprint image comprising means arranged to examine a plurality of predetermined ones of a number of sections of the area of the image to produce for each of the plurality of sections a value related to the number of ridges (or troughs) in a given direction across that section, said number of sections being arranged in rows and columns and the plurality of those sections examined not all being in the same row or column. It is desirable that the same area of a fingerprint be examined each time that a person has his fingerprint classified and so a preferred embodiment incorporates means for restraining a finger against longitudinal displacement and rotation.
  • the image taken of a fingerprint may be a grey scale image and the entirety of the processing may be carried out on that image.
  • the grey scale image can be converted to a pure black and white binary image before the distance or count measurements are made.
  • it is preferable to enhance the grey scale image for example by modifying the grey scale value of each pixel in dependence upon an actual or interpolated value of the maximum and minimum intensities in the neighbourhood of that pixel.
  • Figure 1 shows a fingerprint recording and verifying arrangement
  • Figure 2 is a diagram of a fingerprint aligning arrangement of the apparatus of Figure 1 ;
  • Figure 3 shows a modification of Figure 2 ,
  • Figure 4 is a diagram illustrating a portion of an image of a fingerprint being examined for image enhancement
  • Figure 5 is a diagram illustrating the area of a finger print image examined to obtain its characteristic values?
  • Figure 6 is a flow chart illustrating fingerprint data derivation for storage on a card.
  • Figure 7 is a flow chart illustrating fingerprint verification.
  • Figure 1 illustrates apparatus for capturing the image of a fingerprint, analysing it into characteristic values and then either storing those values on a card for future use or for comparing the characteristic values with those already stored on a card.
  • the apparatus comprises elements which are already on the market and consisting of a card read/write device 1 , a computer 2, an image digitiser 3 and a CCD camera 4.
  • the apparatus also comprises a right-angled prism 5 having a blackened surface 6, a hypotenuse surface 7 to be illuminated by a light source 8 and an upper surface 9 on which a finger is to be placed.
  • finger restraining means are provided more accurately to locate the finger, including a finger restraint 10 for longitudinal alignment of the finger. This restraint incorporates a micro-switch 11 arranged to be actuated when a finger has been placed on the prism in the position shown.
  • a further micro-switch 12 is placed adjacent the prism. It will be apparent that, when the finger is correctly positioned, both micro- switches will be activated and this activation is detected by the computer 2, being represented by an AND gate 13 coupled to the computer. The AND gate 13 also activates the light source 8. Thus, when a finger has been placed correctly on the upper surface 9 of the prism, the light source 8 is activated and the computer is signalled that the image is ready for capture. Where the finger is not touching the face of the prism, the CCD camera will see either a dark or black portion of the image but where the finger is touching the face of the prism, the sweat of the finger causes the light to be reflected to the CCD camera which thus sees these portions as zones of relatively high illumination.
  • the finger restraint 10 above the prism 5 is generally U- shaped to provide lateral and longitudinal restraint for a finger thereby to oppose rotation of the finger and also to ensure that the fingertip has correctly located against the bight of the finger restraint member 10.
  • FIG. 3 is a plan view of an alternative arrangement of finger restraint.
  • the finger restraint member 10 is replaced by three elements, two side restraints 14 and 15 and a rotatable end locator and restraint 16.
  • the element 16 has three alternative arcuate apertures for a large finger at 17, a medium sized finger at 18 and a small finger.at 19. Each of these arcuate recesses incorporates a ledge 20 to accommodate a fingernail.
  • the element 16 is rotatably mounted on a cylindrical member 21 which contains an elliptical bore 22 in which a shaft 23 is mounted for lateral movement along the major.axis of the ellipse 22.
  • Spring means 24 bias the shaft 23.
  • the microswitch 11 is located on the major axis of the ellipse.
  • this image is converted into a black and white binary image where each pixel is represented by a single bit.
  • This process is performed in two steps the first of which is to equalise the intensities of the six bit pixels and the second of which is global thresholding.
  • the image intensity varies across the image due to uneven lighting of the blackened prism face and the face of the prism that the finger is placed on. These variations are of an order of magnitude lower than the frequency of the ridges of a fingerprint.
  • the image is divided into 56 regions each region being of 16x16 pixels.
  • the software in the computer calculates the minimum (U) and the maximum (V) of the intensities and assigns this minimum and maximum to the centre point of 16x16 region.
  • Figure 4 illustrates four such regions for which maxima are shown having values of M-j , M2, M3 and M4.
  • the software calculates an approximate minimum and maximum by linear interpolation between the values for the points shown in Figure 4. The final recorded intensity for the point shown is then calculated to be
  • the computer software carries out the second step, which is global thresholding of the image.
  • the mean of the intensity is found for a region known to contain ridges and troughs, e.g. a central region of the image area, and the whole image is thresholded about this mean.
  • the resulting binary image is now stored in the internal memory of the computer. Digressing to Figure 6, this represents a flow chart of the software in the computer 2 and it will be apparent that the first three steps of Figure 6 correspond to the steps so far described.
  • this diagrammatically shows the area of the image stored in the computer memory and is an area 160 pixels wide (about 1.5 cm) and 192 pixels high (the width being in the x direction across the fingerprint and the height being in the y direction along the length of the fingerprint).
  • this area is a fixed distance from the tip of the fingerprint, and is also centrally placed relative to the fingerprint.
  • this rectangular image represents a trapezoidal area of the fingerprint. If desired this distortion can be removed by known techniques by mapping the image onto a trapezoid of reverse form so that the resulting image in memory is uniformly scaled relative to the original fingerprint.
  • the area shown in Figure 5 and representing the data stored in the computer memory is sub-divided into 30 sections each of 32x32 pixels organised in 8 bit bytes arranged in rows in the x directions.
  • the next step in the processing is to find a characteristic value for each of these 30 regions.
  • a characteristic is found by taking the average of the ridge-to-ridge gaps found using a linear auto-correlation method for 16 points taken in a 4x4 grid in the section. The points are chosen at 8 pixel spacings, starting at the top left of the section.
  • the first point taken is the top left hand corner and the portion of the image to be examined in relation to that point is the 16 x 16 pixel portion 26 shown in dotted lines.
  • each portion such as 26 is chosen to embrace at least 2, and preferably at least 3 y ridges and is an integral member of bytes wide.
  • the bit pattern of the portion 26 is captured and compared with the successive 16x16 portions succeeding one another in the y direction. Each such portion may be 1 pixel displaced from the preceding one. It will be apparent that when the portion 26 is firstly compared with itself a very large value of correlation is found by the comparison. As the distance N increases from the starting point, the comparison will get poorer and a lower correlation value will be obtained until one has moved far enough to be comparing ridges with troughs in which case the comparison reaches a minimum correlation value. Further comparison of subsequent portions in the y direction would then normally give higher and higher correlations until a maximum is reached, whereafter the correlation value will again fall. In this particular embodiment, 27 successive comparisons are made, the objective being to defined a minimum and maximum.
  • Comparison can be made by counting matching pixels, achieved by XORing corresponding bytes and counting the number of Os. To find the number of Os in a byte, a look-up table is used. If one were to plot the correlation value obtained against distance traversed, the general form of the graph would be that of a decaying sinusoid. In practice there will be several small minima and maxima owing to noise, so the process includes the further step of processing the correlation values obtained to achieve a certain amount of smoothing. The process then looks for a minimum followed by a maximum with a difference in value between the two greater than a preselected amount. The distance N travelled upto that maximum is taken as the characteristic value for this specific examination.
  • this value corresponds to the distance between ridges in the portion 26. It is sometimes the case that a local maximum cannot be found reliably by this method and in this case a "gap cannot be found" flag is set and this point is not used to determine the characteristic value of the overall section 25.
  • Another method of finding the gap width is to attempt to fit shapes in the form of decaying sinusoids to the correlation v. distance data.
  • the closest sinusoid has a frequency related to the ridge gap width.
  • the result of this process is 30 values representing the gap characteristic for the 30 sections and 24 values representative of the ridge count along 24 lines.
  • the 54 values are then output by the computer 2 to the card read/write device 1 where they are recorded on a magnetic stripe on a card.
  • the system has been utilised to capture a fingerprint image and obtain, as a series of 54 numbers, a characteristic of a fingerprint for recording on a card for subsequent use in a verification system.
  • the equipment as shown in Figure 1 is still used.
  • the card holder places his card into the card read/write device 1 from which the 54 values are read and stored in the internal memory of the computer.
  • the card holder places his finger on the prism as already described and the finger print is captured by the digitiser.
  • the comparison may be carried out according to the following algorithm:
  • E ⁇ represents the encoded value for section i (i goes from 1 to 30)
  • V_ represents the gap value found for the section i
  • N j _ represents the number of gaps successfully found in section i (N ⁇ is less than or equal to 16). If the magnitude of E_ - V ⁇ is equal to or less than 2 pixels, this magnitude is set to 0.

Landscapes

  • Engineering & Computer Science (AREA)
  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Collating Specific Patterns (AREA)
  • Image Analysis (AREA)

Abstract

On procède à l'analyse d'empreintes digitales par division d'une image d'empreintes digitales en un réseau de parties (26), dont chacune est analysée afin de compter ses crêtes et ses creux et de donner une valeur caractéristique pour chaque partie. Afin d'obtenir une mesure de comptage, on compare la configuration des pixels d'une partie avec des configurations successives s'écartant de cette partie, la distance parcourue pour permettre une corrélation maximum avec la partie originale étant utilisée comme valeur caractéristique. On peut utiliser de telles valeurs pour l'identification d'empreintes digitales et dans un système de vérification, par exemple par stockage des valeurs caractéristiques d'une personne sur une carte d'identité.
EP88908740A 1987-10-05 1988-10-05 Procede et appareil d'analyse d'empreintes digitales Withdrawn EP0333826A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GB878723299A GB8723299D0 (en) 1987-10-05 1987-10-05 Identity verification
GB8723299 1987-10-05

Publications (1)

Publication Number Publication Date
EP0333826A1 true EP0333826A1 (fr) 1989-09-27

Family

ID=10624787

Family Applications (1)

Application Number Title Priority Date Filing Date
EP88908740A Withdrawn EP0333826A1 (fr) 1987-10-05 1988-10-05 Procede et appareil d'analyse d'empreintes digitales

Country Status (5)

Country Link
EP (1) EP0333826A1 (fr)
JP (1) JPH02501684A (fr)
AU (1) AU2539688A (fr)
GB (1) GB8723299D0 (fr)
WO (1) WO1989003099A1 (fr)

Families Citing this family (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB9006370D0 (en) * 1990-03-21 1990-05-16 Emi Plc Thorn Fingerprint characterization technique
JPH04252383A (ja) * 1990-07-27 1992-09-08 Ezel Inc 指紋撮影装置
US5261008A (en) * 1990-08-07 1993-11-09 Yozan, Inc. Fingerprint verification method
DE69124312T2 (de) * 1990-08-07 1997-05-07 Sharp Kk Verfahren zur Prüfung von Fingerabdrücken
FR2671210A1 (fr) * 1990-12-28 1992-07-03 Villa Pierre Procede d'identification et d'authentification d'informations caracterisant un individu.
US5633947A (en) * 1991-03-21 1997-05-27 Thorn Emi Plc Method and apparatus for fingerprint characterization and recognition using auto correlation pattern
US5237621A (en) * 1991-08-08 1993-08-17 Philip Morris Incorporated Product appearance inspection methods and apparatus employing low variance filter
NL9200439A (nl) * 1992-03-10 1993-10-01 Vr Opto B V Fraude bestendige inrichting.
US5729334A (en) * 1992-03-10 1998-03-17 Van Ruyven; Lodewijk Johan Fraud-proof identification system
GB2267771A (en) * 1992-06-06 1993-12-15 Central Research Lab Ltd Finger guide
DE4421243A1 (de) * 1993-06-21 1994-12-22 Asahi Optical Co Ltd Einrichtung zur Eingabe eines Fingerabdrucks
SG122737A1 (en) * 2000-06-14 2006-06-29 Univ Singapore Apparatus and method for compressing and decompressing fingerprint information
CN113569715B (zh) * 2021-07-23 2024-04-16 北京眼神智能科技有限公司 一种指纹图像增强方法及装置

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4151512A (en) * 1976-09-10 1979-04-24 Rockwell International Corporation Automatic pattern processing system
US4581760A (en) * 1983-04-27 1986-04-08 Fingermatrix, Inc. Fingerprint verification method
US4607384A (en) * 1984-05-01 1986-08-19 At&T - Technologies, Inc. Fingerprint classification arrangement
US4641350A (en) * 1984-05-17 1987-02-03 Bunn Robert F Fingerprint identification system
AU587152B2 (en) * 1985-08-16 1989-08-03 Malcolm K. Sparrow Fingerprint recognition and retrieval system
GB8609620D0 (en) * 1986-04-19 1986-05-21 Wheatley M R H Identity verification

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See references of WO8903099A1 *

Also Published As

Publication number Publication date
AU2539688A (en) 1989-04-18
JPH02501684A (ja) 1990-06-07
GB8723299D0 (en) 1987-11-11
WO1989003099A1 (fr) 1989-04-06

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