fingerprint technology


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fingerprint technology

  1. 1. APRESENTATIONonFingerprint RecognisationFingerprint RecognisationTechnologyTechnology(f.r.t)(f.r.t)BY:-VISHWAS JANGRA5909407ECE(8THSEM)
  2. 2. Introduction: Definition of Biometrics:-“Automated methods of recognizing a person based on aphysiological or behavioral characteristics”.“ The technology used for identification of a user based on aphysical or behavioral characteristic, such as a fingerprint, iris,face, voice or handwriting is called Biometrics”.
  3. 3. 3History of fingerprintsHuman fingerprints have been discovered on a large number ofarchaeological artifacts and historical itemsIn 1684, the English plant morphologist, Nehemiah Grew, publishedthe first scientific paper reporting his systematic study on the ridge,furrow, and pore structureIn 1788, a detailed description of the anatomical formations offingerprints was made by Mayer.In 1823, Purkinji proposed the first fingerprint classification, whichclassified into nine categoriesIn 1975, The FBI funded the development of fingerprint scanners
  4. 4. Why FINGER PRINT?Oldest form of BiometricsHigh ReliablityUses distinctive features of fingers
  5. 5. Fingerprint Formation
  6. 6. 6Fingerprint sensingBased on the mode of acquisition, a fingerprint image is classified asOff line imageLive-scan imageThere are a number of live-scan sensing mechanisms that can detect theridges and valleys present in the fingertipExamples areOptical FTIRCapacitivePressure-basedUltrasound
  7. 7. • classification is necessary to reduce the search time and computationalcomplexity.• The FBI database has 70 million fingerprints.Fingerprint ClassificationRight Loop WhorlArch
  8. 8. 8The general structure of fingerprint scanner
  9. 9. DevicesOptical fingerprint sensorFIU-001/500 by SONYElectro-optical sensor[DELSY® CMOS sensor modul]Capacitive sensor[FingerTIP™ by Infineon][ID Mouse by Siemens]Keyboard [G 81-12000by Cherry]
  10. 10. 10
  11. 11. Fingerprint SensorsOpticalSilicon Based Capacitive SensorsUltrasoundThermalPyroelectricPiezo-electric
  12. 12. Parameters characterizing a fingerprintdevice are Resolution Area Number of pixels Geometric Accuracy Image Quality Interface Frames per second Automatic finger detection Encryption Supported operating systems
  13. 13. Optical SensorsOldest and most widely used technology.Majority of companies use optical technology.The finger is placed on a coated hard plastic plate.In most devices, a charged coupled device (CCD) converts the image ofthe fingerprint, with dark ridges and light valleys, into a digital signal.The brightness is either adjusted automatically or manually, leading to ausable image.
  14. 14. Optical Sensors-contd..Advantages• They can withstand, to some degree temperature fluctuations.• They are fairly inexpensive.• They can provide resolutions up to 500 dpi.Disadvantages• Size, the sensing plate must be of sufficient size to achieve aquality image• Residual prints from previous users can cause image degradation,as severe latent prints can cause two sets of prints to besuperimposed.• The coating and CCD arrays can wear with age, reducing accuracy.• A large number of vendors of fingerprint sensing equipment aregradually shifting towards silicon-based technology.
  15. 15. Silicon Based Sensors• Silicon technology has gained considerable acceptance since itsintroduction in the late 90s.• Most silicon, or chip, technology is based on DC Capacitance, butsome also use AC Capacitance.• The silicon sensor acts as one plate of a capacitor, and the finger isthe other.• The capacitance between the sensing plate and the finger isconverted into an 8-bit grayscale digital image.
  16. 16. Silicon Based Sensors-contd..• Fingerprint cards contain numerous capacitive plates which measurethe capacitance between the plates and the fingertip.• When the finger is placed on the sensor extremely weak electricalcharges are created, building a pattern between the fingers ridges orvalleys and the sensors plates.• Using these charges the sensor measures the capacitance patternacross the surface.• The measured values are digitized by the sensor then sent to theneighboring microprocessor.• This can be done directly by applying an electrical charge to theplate or by using electronic pulses passed to the fingertip.
  17. 17. Silicon Based Sensors-contd..Advantages• The Silicon chip comprises of about 200*200 lines on a wafer the sizeof 1cm*1.5cm, thus providing a pretty good resolution for the image.• Hence, Silicon generally produces better image quality, with less surfacearea, than optical.• Also, the reduced size of the chip means lower costs.• Miniaturization of Silicon chips also makes it possible for the chips tobe integrated into numerous devices.Disadvantages• In spite of claims by manufacturers that Silicon is much more durablethan optical, Silicons durability, especially in sub-optimal conditions,has yet to be proven.• Also, with the reduction in sensor size, it is even more important toensure that enrolment and verification are done carefully.
  18. 18. Ultrasound Sensors• Ultrasound technology is perhaps the most accurate of thefingerprint technologies.• It uses transmitted ultrasound waves and measures the distancebased on the impedance of the finger, the plate, and air.
  19. 19. Ultrasound Sensors-contd..AdvantagesUltrasound is capable of penetrating dirt and residue on the sensing plateand the finger.This overcomes the drawbacks of optical devices which cant make thatdistinction.It combines a strength of optical technology-large platen size and ease ofuse, with a strength of silicon technology-the ability to overcome sub-optimal reading conditions.It is also virtually impossible to deceive an ultrasound system.DisadvantagesThe quality of the image depends to a great extent on the contactbetween the finger and the sensor plate.Scanner is largeMechanical parts are quite expensive
  20. 20. Thermal Sensors• Uses Pyro Electric material.• Pyro-electric material is able to convert a difference intemperature into a specific voltage.• This effect is quite large, and is used in infraredcameras.• A thermal fingerprint sensor based on this materialmeasures the temperature difference between the sensorpixels that are in contact with the ridges and thoseunder the valleys, that are not in contact.
  21. 21. Thermal Sensors-contd..Advantages• A strong immunity to electrostatic discharge• Thermal imaging functions as well in extreme temperature conditions asat room temperature.• It is almost impossible to deceive with artificial fingertips.Disadvantages• A disadvantage of the thermal technique is that the image disappearsquickly.• When a finger is placed on the sensor, initially there is a big difference intemperature, and therefore a signal, but after a short period (less than atenth of a second), the image vanishes because the finger and the pixelarray have reached thermal equilibrium.• However, this can be avoided by using a scanning method where thefinger is scanned across the sensor which is the same width as the imageto be obtained , but only a few pixels high.
  22. 22. 22Piezo- Electric sensorsPressure sensitive sensorsProduce an electrical signal when mechanical stress is appliedto themSensor surface is made up of a non-conducting dielectricmaterialRidges and valleys are present at different distances from thesurface , they result in different amounts of current
  23. 23. 24Storing & Compressing fingerprintimagesEach fingerprint impression produces an image of 768 x 768( when digitized at 500 dpi)In AFIS applications, this needs more amount of memoryspace to store these imagesNeither lossless methods or JPEG compression techniques aresatisfactoryA new compression technique called Wavelet ScalarQuantization (WSQ) is introduced to compress the images
  24. 24. 25WSQBased on Adaptive scalar quantizationPerforms following stepsFingerprint image is decomposed into a number of spatialfrequency sub-bands using a Discrete wavelet transformthe resulting DWT coefficients are quantized into discrete valuesthe quantized sub-bands are concatenated into several blocks andcompressed using an adaptive Huffman-run length encodingA compressed image can be decoded into the original image byapplying steps in reverse orderWSQ compress a fingerprint image by a factor of 10 to 25.
  25. 25. Feature EnhancementThe first step is to obtain a clear image of the fingerprint.Enhancement is carried out so as to improve the clarity of ridge andfurrow structures of input fingerprint images based on the estimatedlocal ridge orientation and frequency.For grayscale images, areas lighter than a particular threshold arediscarded, and those darker are made black.Original Enhanced
  26. 26. • Minutiae localization is the next step.•Even a very precise image has distortions and false minutiae that need to be filtered out.•Anomalies caused by scars, sweat, or dirt appear as false minutiae, and algorithmslocate any points or patterns that dont make sense, such as a spur on an island or a ridgecrossing perpendicular to 2-3 others (probably a scar or dirt).•A large percentage of would-be minutiae are discarded in this process.• The point at which a ridge ends, and the point where a bifurcation begins, are themost rudimentary minutiae. Once the point has been situated, its location is commonlyindicated by the distance from the core, with the core serving as the 0,0 on an X,Y-axis.In addition to the placement of the minutia, the angle of the minutia is normally used.When a ridge ends, its direction at the point of termination establishes the angle. Thisangle is taken from a horizontal line extending rightward from the core, and can be up to359.• In addition to using the location and angle of minutiae, some classify minutia by typeand quality. The advantage of this is that searches can be quicker, as a particularlynotable minutia may be distinctive enough to lead to a match. [6]
  27. 27. •The matching accuracy of a biometrics-based authentication system relies on thestability of the biometric data associated with an individual over time.•The biometric data acquired from an individual is susceptible to changes introduceddue to improper interaction with the sensor (e.g., partial fingerprints), modificationsin sensor characteristics (e.g., optical vs. solid-state fingerprint sensor), variations inenvironmental factors (e.g.,dry weather resulting in faint fingerprints) and temporaryalterations in the biometric trait itself (e.g., cuts/scars on fingerprints).•Thus, it is possible for the stored template data to be significantly different from thoseobtained during authentication, resulting in an inferior performance (higher falserejects) of the biometric system.Variation in fingerprint exhibiting partial overlap.
  28. 28. •Multiple templates, that best represent the variability associated with a usersbiometric data, should be stored in the database. (E.g. One could store multipleimpressions pertaining to different portions of a users fingerprint in orderto deal with the problem of partially overlapping fingerprints.)• There is a tradeoff between the number of templates, and the storage andcomputational overheads introduced by multiple templates.•For an efficient functioning of a biometric system, this selection of templatesshould be done automatically.•There are two methods that are discussed in the literature. Please refer toreferences for further details.Template Selection-contd..(Solutions to variations)
  29. 29. •Automatic Minutiae Detection: Minutiae are essentially terminations andbifurcations of the ridge lines that constitute a fingerprint pattern.•Automatic minutiae detection is an extremely critical process, especially in low-quality fingerprints where noise and contrast deficiency can originate pixelconfigurations similar to minutiae or hide real minutiae.Algorithm:•The basic idea here is to compare the minutiae on thetwo images.•The figure alongside is the input given to the system,as can be seen from the figure the various details ofthis image can be easily detected. Hence, we are in aposition to apply the AMD algorithm.
  30. 30. Algorithm (contd.)• The next step in the algorithm is tomark all the minutiae points on theduplicate image of the input fingerprintwith the lines much clear after featureextraction.• Then this image is superimposedonto the input image with markedminutiae points as shown in the figure.• Finally a comparison is made with theimages in the database and aprobabilistic result is given.
  31. 31. • It is difficult to extract the minutiae points accurately when thefingerprint is of low quality.•This method does not take into account the global pattern ofridges and furrows.• Fingerprint matching based on minutiae has problems inmatching different sized (unregistered) minutiae patterns.
  32. 32. Hardware Solution•Temperature sensing, detection of pulsation on fingertip, pulse oximetry,electrical conductivity, ECG, etc.Software Solution (Research going on)•Live fingers as opposed to spoofed fingers show some kind of moisturepattern due to perspiration.•The main idea behind this method is to take two prints after a time frame ofsay 5 seconds and the algorithm makes a final decision based on the vitalityof the fingerprint.
  33. 33. •Banking Security - ATM security,card transaction•Physical Access Control (e.g. Airport)•Information System Security•National ID Systems•Passport control (INSPASS)•Prisoner, prison visitors, inmate control•Voting•Identification of Criminals•Identification of missing children•Secure E-Commerce (Still under research)
  34. 34. Latest Technologies3-D fingerprintA new generation of touchless live scan devices that generatea 3D representation of fingerprints is appearing.Several images of the finger are acquired from different viewsusing a multicamera system, and a contact-free 3Drepresentation of the fingerprint is constructed.This new sensing technology overcomes some of theproblems that intrinsically appear in contact-based sensorssuch as improper finger placement, skin deformation, sensornoise or dirt.
  35. 35. 1) Biometric systems lab - Biometrica - International Biometric Group – reports/finger-scan_extraction.html4) Dr. Dirk Scheuermann - “”5) Handbook of fingerprint recognition - D. Maltoni, D. Maio, A. K. Jain, S. Prabahakar - Springer – 20036) - “Issues for liveliness detection in Biometrics” - Stephanie Schuckers, Larry Hornak,Tim Norman, Reza Derakhshani,Sujan Parthasaradhi8) “Overview of Biometrics & Fingerprint Technology” - Dr. Y.S. Moon9) “Biometric Template Selection: A Case Study in Fingerprints” - Anil Jain, Umut Uludag and Arun Ross Fingerprint Registry Service - Rideology and Poroscopy - Multibiometric Systems - Anil K. Jain and Arun Ross
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