Advances in Fingerprint Technology.pdf

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37. Siemens. The ID Mouse from Siemens. http://www.fingertip.de/. 38. American National Standard for Information Systems. Data Format for the Interchange of Fingerprint Information, Doc#ANSI/NIST-CSL 1-1993, Appendices F and G. ftp://ard.fbi.gov/pub/IQS/spec/. America National Standards Institute, New York, 1993. 39. Criminal Justice Information Services. Interim IAFIS Image Quality Specifications for Scanners. www.engr.sjsu.edu/biometrics/publications_appendixg. html. 40. A.K. Jain, S. Prabhakar, L. Hong, and S. Pankanti. Filterbank-based fingerprint matching. IEEE Trans. Image Processing, 9(5), 846–859, May 2000. 41. Access Control Applications Using Optical Computing. http://www.mytec. com/, 1997. 42. American National Standard for Information Systems. Data Format for the Interchange of Fingerprint Information, doc#ansi/nist-csl itl 2000, NIST special report 500, 245, 2000. 43. E. German. Problem Idents. Facial and scar mark and tattoo (SMT) http://onin.com/fp/problemidents.html. 44. R.M. Bolle, S. Pankanti, and Y.-S. Yao. System and Method for Determining the Quality of Fingerprint Images, U.S. Patent No. 5,963,656, 1999. 45. R.M. Bolle, S.E. Colville, and S. Pankanti. System and Method for Determining Ridge Counts in Fingerprint Image Processing. U.S. Patent No. 6,111,978, 2000. 46. M. Kawagoe and A. Tojo. Fingerprint pattern classification. Pattern Recognition, 17(3), 295–303, 1984. 47. B.M. Mehtre and B. Chatterjee. Segmentation of fingerprint images — a composite method. Pattern Recognition, 22(4), 381–385, 1989. 48. S. Chen, N. Ratha, K. Karu, and A.K. Jain. A real-time matching system for large fingerprint database. IEEE Trans. Pattern Anal. and Machine Intell., 18(8), 799–813, 1996. 49. T. Pavlidis. Algorithms for Graphics and Image Processing. Computer Science Press. 1982. 50. G.T. Candela, P.J. Grother, C.I. Watson, R.A. Wilkinson, and C.L. Wilson. PCASYS: A Pattern-Level Classification Automation System for Fingerprints. NIST-Tech. Report NISTIR 5647, August 1995. 51. R. Germain, A. Califano, and S. Colville. Fingerprint matching using transformation parameter clustering. IEEE Computational Science and Engineering, 4(4), 42–49, 1997. 52. A.K. Jain, S. Prabhakar, and L. Hong. A multichannel approach to fingerprint classification. IEEE Trans. Pattern Anal. and Machine Intell., 21(4), 348–359, April 1999.
53. M. Sparrow and P. Sparrow. A Topological Approach to the Matching of Single Fingerprints: Development of Algorithms for Use on Latent Fingermarks, U.S. Government Publication. Gaithersburg, MD: U.S. Dept. of Commerce, National Bureau of Standards, Washington, D.C., 1985. 54. J.H. Wegstein. An Automated Fingerprint Identification System. Technical Report 500-89, National Bureau of Standards, 1982. 55. L. O’Gorman and J.V. Nickerson. An approach to fingerprint filter design. Pattern Recognition, 22(1), 29–38, 1989. 56. T. Kamei and M. Mizoguchi. Image filter design for fingerprint enhancement. In Proc. ISCV ’95, Coral Gables, FL, 1995, 109–114. 57. D.C. Huang. Enhancement and feature purification of fingerprint images. Pattern Recognition, 26(11), 1661–1671, 1993. 58. L. Coetzee and E. Botha. Fingerprint recognition in low quality images. Pattern Recognition, 26(10), 1441–1460, 1993. 59. L. Hong, A.K. Jain, S. Pankanti, and R. Bolle. Fingerprint enhancement. In Proc. 1st IEEE WACV, Sarasota, FL, 1996, 202–207. 60. A.K. Jain and F. Farrokhnia. Unsupervised texture segmentation using Gabor filters. Pattern Recognition, 24, 1167–1186, 1991. 61. J.L. Wayman. Fundamentals of Biometric Technology. http://www.engr. sjsu.edu/biometrics/publications.html. 62. UK Govt. Biometrics Working Group. Best Practices in Testing and Reporting Biometric Device Performance, version 1.0. http://www.afb.org.uk/bwg/ bestprac10.pdf, March 2000. 63. P.J. Phillips, H. Moon, S.A. Rizvi, and P.J. Rauss. The FERET evaluation methodology for face recognition algorithms. IEEE Trans. on Pattern Anal. Mach. Intell., 22(10), 1090–1104, 2000. 64. J.G. Daugman. High confidence visual recognition of persons by a test of statistical independence. IEEE Trans. on Pattern Anal. Mach. Intell., 15(11), 1148–1161, 1993. 65. J.G. Daugman and G.O. Williams. A proposed standard for biometric decidability. In Proc. CardTech/SecureTech Conf., Atlanta, GA, 1996, 223–234. 66. J. Campbell Jr., L. Alyea, and J. Dunn. Biometric Security: Government Applications and Operations. http://www.biometrics.org/REPORTS/CTSTG96/ index.html, 1996. 67. A.K. Jain, S. Prabhakar, and S. Chen. Combining multiple matchers for a high security fingerprint verification system. Pattern Recognition Lett., 20(11–13), 1371–1379, 1999. 68. S. Prabhakar and A.K. Jain. Devision-level fusion in biometric verification. To appear in Pattern Recognition, 2001.
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Advances in Advances Fingerprint Te
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Advances in Fingerprint Technology
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Preface The first edition of this b
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Acknowledgments We gratefully ackno
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Table of Contents Preface Acknowled
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History and Development of Fingerpr
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Figure 1.2 Basic fingerprint patter
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Figure 1.3 Portion of the prehensil
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Figure 1.4 Elliptical whorl. Theory
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The bricks, carefully laid and accu
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the megalithic builders, including
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made most of them. These “identif
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Figure 1.6 Nehemiah Grew. (Drawn by
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Figure 1.7 Right palm imprint in pl
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By kindly words of persuasion a ref
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Loop: Now if this oblique stripe by
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Figure 1.11 Dr. Ivan Vucetich. (Dra
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Sir Edward Henry and Sir William He
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in charge he undoubtedly supported
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1. Finding finger imprints on prehi
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Faulds edited seven issues of a fin
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much of his inspired research. For
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to the unrelenting efforts of Steeg
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and gathered around him a nucleus o
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I find that portions of palm imprin
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Identification of Latent Prints ROB
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Without it, no amount of further la
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work will quite often fare badly un
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Figure 2.3 Polygon method. Overlay
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Experience and Skill Although the t
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The initial identification of the l
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D5 D6 D7 I2 D8 D9 D10 No No No Reco
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D11 I4 No D12 D11 I5 D12-1 D7 D12-2
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D14 I7 D16 C3 D11 D14-2 D7 D14-3 C2
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Figure 2.7 Example of pressure dist
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9. Mairs, G., Novel method of print
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DNA From Latent Prints DNA From Blo
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Figure 3.1 A schematic diagram show
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Figure 3.3 A schematic diagram of t
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(5 to 12 µg/L), bromide (0.2 to 0.
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electrophoresis (SDS-PAGE) include
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Table 3.3 Anatomical Variation in t
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Various oxidative and bacteriologic
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acid content can change with time i
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are of sebaceous origin. 82 Approxi
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Table 3.7 Changes in Surface Lipid
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gland’s activity. The more active
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content. 108 Palmitic acid was foun
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Figure 3.4a A chromatogram of a fin
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various lipid classes found in a la
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of DNA using RFLP. 130 No adverse e
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was later found to be caused by the
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17. Seutter, E., Goedhart-De Groot,
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52. Downing, D. T., Strauss, J. S.,
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85. Summerly, R., Yardley, H. J., R
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120. Duff, J. M. and Menzel, E. R.,
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149. Kloosterman, A., Application o
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Coumarin 540 Dye Staining Method An
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visualization of latent fingerprint
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White powder Dolomite, starch powde
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Fluorescein solution (in methanol/w
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Notes: Dissolve the MoS 2 in the di
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4. Avoid inhaling any iodine fumes
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CN CN CN A - A - CH2 C COOR CH2 C C
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Large vacuum chambers for processin
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Gentian Violet Solution — Non-Phe
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Table 4.1 Approximate Absorption an
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and recorded by autoradiography. Ni
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Ninhydrin solutions may be applied
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of development of ninhydrin-treated
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and certain nonreactive surface mat
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Procedure Xylene 50 mL Petroleum et
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ehavior of Ruhemann’s purple-meta
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4. Rinse the specimen in tap water.
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een treated with ninhydrin. In addi
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Working solution Stock solution 6 m
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Note: Combine and stir until citric
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Zauner 181 noted that on a rare occ
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3. Expose the tape surface to a hig
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lifting media were used, followed b
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under certain circumstances. The Br
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Physical Methods Visual Examination
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DRY Super Glue Fuming Powder Dustin
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Visual Examination Photography Iodi
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References 1. Olsen, R. D., Scott
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36. Springer, E. and Bergman, P., A
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74. McCarthy, M. M., Evaluation of
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110. Mooney, D. G., Development of
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142. Pounds, C. A., Grigg, R., and
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175. Jones, R. J. and Pounds, C. A.
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213. Hebrard, J. and Donche, A., Fi
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245. Misner, A., Wilkinson, D., and
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Fingerprint Development by Ninhydri
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Figure 5.1 2,2-Dihydroxy-1,3-indane
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Figure 5.4 Formation of murexide (V
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Figure 5.6 The 1,3-dipole form of t
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less volatile 1,1,2-trichloroethane
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Key to Routes Primary Special Secon
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Specially designed cabinets for che
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the importance of cooling the objec
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Figure 5.10 Ninhydrin (I) and some
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een prepared and evaluated as finge
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Figure 5.14 The red pigment formed
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Figure 5.16 The fluorescent product
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16. Pounds, C.A. and Jones, R.J., P
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51. Jungbluth, W.O., Replacement fo
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87. Kent, T., An operational guide
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116. Kobus, H.J., Pigou, P.E., Dell
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147. Dayan, S., Almog, J., Khodzhae
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Figure 6.1 Ninhydrin/ZnCl 2 vs. nin
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purposes of understanding their pho
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Ar-laser image monitor lens light c
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laser Figure 6.6 Block diagram of p
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step 1 step 2 step 3 fingerprint co
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nanocrystals. Photoluminescent semi
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Figure 6.11 Photoluminescence of fi
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H H H H N N CH2CH2 CH2CH2 H N N H N
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sample, rather than preferential ad
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O R C OH + R' NH2 R C Figure 6.16 G
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The amidation reaction depicted in
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R 1 - COOH + HO - N R 1 O C N H Fig
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29. Sooklal, K., Hanus, L.H., Ploeh
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Procedure Water and Acid Pretreatme
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The Silver Physical Development Pro
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(in the emulsion) the silver and si
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ions (found only on paper that has
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as that of print residue on porous
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+ + + + + + + Cit 3- Cit 3- Cit 3-
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Saunders. 22 Both workers recognize
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Figure 7.2 Scanning electron micros
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paper and these convert to ferric o
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Water and Acid Pretreatments The wa
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Figure 7.4 Comparison of a ninhydri
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Figure 7.7 Comparison of a ninhydri
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(0.2%) to not form silver oxide whe
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X-Ray and Scanning Electron Microsc
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is much to be done to optimize the
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3. Margot, P. and Lennard, C., Fing
Page 284 and 285: 35. Morris, J.R. and Wells, J.M., A
Page 286 and 287: Introduction More than a century ha
Page 288 and 289: False Reject Rate (FRR) Civilian Ap
Page 290 and 291: Fingerprint Quality Acquisition Est
Page 292 and 293: finger gets mapped onto the two-dim
Page 294 and 295: (a) (b) (c) Figure 8.3 Fingerprint
Page 296 and 297: In forensics, a special kind of ink
Page 298 and 299: L A B (a) Finger Friction Surface R
Page 300 and 301: Fingerprint Representation A finger
Page 302 and 303: (a) (b) (c) (d) Figure 8.8 A finger
Page 304 and 305: Figure 8.10 Relative configuration
Page 306 and 307: A minutiae feature extractor finds
Page 308 and 309: depicting a ridge in the fingerprin
Page 310 and 311: 1. Singular points. The Poincare in
Page 312 and 313: Table 8.2 shows the results of the
Page 314 and 315: (a) (b) Figure 8.13 Two different i
Page 316 and 317: ox size is adjusted based on the es
Page 318 and 319: (a) (b) Figure 8.16 Fingerprinting
Page 320 and 321: 0.5 -0.5 -1 200 1 0.8 0.6 0.4 0.2 1
Page 322 and 323: andpass filters and extracts ridges
Page 324 and 325: (a) (b) Figure 8.19 Examples of enh
Page 326 and 327: A significant implication of the ab
Page 328 and 329: or otherwise. Therefore, there are
Page 330 and 331: Conclusions and Future Prospects Fi
Page 332 and 333: WSQ-related illustrations (Figure 8
Page 336 and 337: 69. L. Hong, A. Jain, and S. Pankan
Page 338 and 339: Trauring Model (1963) Description o
Page 340 and 341: correspondence in friction ridge de
Page 342 and 343: extreme variability of friction rid
Page 344 and 345: 5. Trauring 19 6. Kingston 20 7. Os
Page 346 and 347: variation need have no relationship
Page 348 and 349: 1. Fork directed to the right 2. Fo
Page 350 and 351: e closer to reality. In any case, t
Page 352 and 353: There is not only opportunity for c
Page 354 and 355: that, in practice, it is relative d
Page 356 and 357: e the probability that there will b
Page 358 and 359: Correction factors (G) were introdu
Page 360 and 361: fingerprint individuality into two
Page 362 and 363: appreciated that the number of tria
Page 364 and 365: a corresponding reference point is
Page 366 and 367: Table 9.1 Kingston’s Relative Fre
Page 368 and 369: minutia counts in different-sized r
Page 370 and 371: If one is to use the compound forms
Page 372 and 373: Osterburg Model (1977-1980) Descrip
Page 374 and 375: of any occurrences that appear in t
Page 376 and 377: minutiae. Both the Kingston and Ost
Page 378 and 379: minutia orientation results in regi
Page 380 and 381: Orientation for minutiae was define
Page 382 and 383: the allowable combinations of minut
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selected for the study, based on th
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Table 9.4 Champod’s Upper Bound F
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that Champod and Margot proved to b
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fingerprint was isolated. This area
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that, for the experiments as design
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can be encouraged by the dedication
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37. Amy, L., Valeur de la preuve en
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The Expert Fingerprint Witness ROBE
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Qualifications of the Fingerprint E
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7. Results of comparisons conducted
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granted for a pretrial conference,
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any examination that I have conduct
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to fully understand the meaning of
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When seated in the witness stand, t
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jury but looked down at the floor i
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Courtroom Courtesy When in court, i
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If the attorney does not have the p
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Glossary of Commonly Used Courtroom
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Indictment An accusation in writing
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APPENDIX Daubert Hearings EDWARD GE
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The U.S. Government set presented e
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Presided over by the Honorable J. C
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