Biometric Quality Reading Material

This page lists reports, white papers, publications and product descriptions relevant to biometric quality. The content is under active development, and NIST welcomes the submission of any additional, citations, links, or copies of such for inclusion on this page.,

Applications

1. E. Tabassi, P.J. Grother, and G.W. Quinn. When to Fuse Two Biometrics, IEEE Computer Society on Computer Vision and Pattern Recognition, Workshop on Multi-Biometrics, September 2006.

2. K. Kryszczuk and A. Drygajlo., Improving classification with class-independent quality measures: Qstack in face verification. Proc. of the 2nd International Conference in Biometrics ICB2007, Seoul Korea, August 2007.

3. K. Kryszczuk and A. Drygajlo., Q-stack: uni- and multimodal classifier stacking with quality measures., Proc. of the International Workshop on Multiple Classifier Systems (MCS 2007), pp. 367-376, Prague, Czech Republic, 2007.

4. R. Cappelli, M. Ferrara, and D. Maltoni., The quality of fingerprint scanners and its impact on the accuracy of fingerprint recognition algorithms., Proc. Multimedia Content Representation, Classification and Security (MRCS) 2006.

5. M. Chan, R. Brown, and W. Turner., Incorporating quality metrics in multimodal biometric fusion., Proc. IEEE Workshop on Biometrics, in assosiacyion with CVPR, July 2006.

6. A. Hicklin and R. Khanna., The role of data quality in biometric systems., Mitretek Systems, February, 2006.

7. J. Fierrez-Aguilar, Y. Chen, J. Ortega-Garcia and A. K. Jain., Incorporating image quality in multi-algorithm fingerprint verification., Proc. IAPR International Conference on Biometrics (ICB), vol. Springer LNCS-3832, pp. 213-2207, Hong Kong, January 5-7, 2006.

8. L. Wein and M. Baveja., Using fingerprint image quality to improve the identification performance of the U.S. VISIT program., Proc. of the National Academy of Sciences, 2005.

9. J. Fierrez-Aguilar, J. Ortega-Garcia, J. Gonzalez-Rodriguez, and Josef Bigun., Discriminative multimodal biometric authentication based on quality measures., Pattern Recognition, 38(5):777–779, May 2005.

10. T. Ko and R. Krishnan., Monitoring and reporting of fingerprint image quality and match accuracy for a large user application., In Proceedings of the 33-rd Applied Image Pattern Recognition Workshop, pages 159–164. IEEE Computer Society, 2004.

11. R. A. Hicklin and C. L. Reedy., Implications of the IDENT/IAFIS Image Quality Study for Visa Fingerprint Processing., Mitretek Systems, October 31, 2002.

12. L. Nadel et al., Image Quality Study Final Report., IDENT/IAFIS Engineering/System Development Study. Mitretek Systems, December 7, 2000.

Biometric Quality Algorithms

1. F. Alonso-Fernandez, J. Fierrez, J. Ortega-Garcia, J. Gonzalez-Rodriguez, H. Fronthaler, K. Kollreider, and J. Bigun., A comparative study of fingerprint image-quality estimation methods., IEEE Transaction on Information Forensics and Security, Vol. 2, n. 4, pp. 734-743, December 2007.

2. D. Van der Weken, M. Nachtegael, and E. Kerre., Combining neighborhood-based and histogram simiarity measures for the design of image quality measures., Image and Vision Computing, vol. 25, pp. 184-195, 2007.

3. R. Youmaran and A. Adler., Measuring biometric sample quality in terms of biometric information., Proc. IEEE Biometrics Symposium, September 2006.

4. K. Kryszczuk and A. Drygajlo., On combining evidence for reliability estimation in face verification., Proc. of the 14th European Conference on Signal Processing (EUSIPCO 2006), Florence, Italy, September 2006.

5. H. Fronthaler, K. Kollreider, and J. Bigun., Automatic image quality assessment with application in biometrics., Proc. IEEE Workshop on Biometrics, in assosiacyion with CVPR, p. 30-35, 2006.

6. K. Kryszczuk and A. Drygajlo., On face quality measures., Proc. 2nd Workshop on Multimodal User Authentication (MMUA'06), Toulouse, France, May 2006.

7. A. Adler and T. Dembinsky., Human vs. automatic measurement of biometric sample quality, Electrical and Computer Engineering, Canadian Conference on, pp. 2090-2093, May 2006.

8. Y. Chen, S. Dass and A. Jain., Localized Iris Image Quality Using 2-D Wavelets., Proc. of International Conference on Biometrics (ICB), Hong Kong, January 5-7, 2006.

9. Z. Sanqiang and G. Yongsheng., Automated Face Pose Estimation Using Elastic Energy Models., International Conference on Pattern Recognition,pp. 618-621, 2006.

10. N. D. Kalka, V. Dorairaj, Y. N. Shah, N. A. Schmid and B. Cukic, Image Quality Assessment for Iris Biometric., Presented at Biometric Consortium Research Symposium, 2005.

11. J. Fierrez-Aguilar, L.M. Muñoz-Serrano, F. Alonso-Fernandez, and J. Ortega-Garcia., On the effects of image quality degradation on minutiae and ridge-based automatic fingerprint recognition., IEEE International Carnahan Conference on Security Technology, pp. 79-82, October 2005.

12. E. Tabassi and C. L. Wilson., A novel approach to fingerprint image quality., IEEE International Conference on Image Processing (ICIP), vol. 2, pp. 37-40, Genoa, Italy, September 2005.

13. Y. Chen, S. Dass and A. Jain., Fingerprint quality indices for predicting authentication performance., Proc. of Audio- and Video-based Biometric Person Authentication (AVBPA), pp. 160-170, Rye Brook, NY, July 2005.

14. T. Chen, X. Jiang, and W. Yau., Fingerprint image quality analysis., Proc. IEEE International Conference on Image processing (ICIP), pp. 1253-1256, 2004.

15. H. Li, M. Zhou, and G. Geng., Rapid pose estimation of Mongolian faces using projective geometry., Proc. Applied Imagery Pattern Recognition Workshop, pp. 171-176 2004.

16. E. Lim, K. Toh, P.Suganthan, X. Jiang, and W. Yau., Fingerprint image quality analysis., Proc. IEEE International Conference on Image processing (ICIP), pp. 1241-1244, 2004.

17. E. Tabassi, C. L. Wilson and C. I. Watson., Fingerprint Image Quality, NFIQ., National Institute of Standards and Technology, NISTIR 7151, 2004.

18. Z. Shi, Y. Wang, J. Qi, and K. Xu., A new segmentation algorithm for low quality fingerprint image., Proc. IEEE International Conference on Image and Graphics (ICIG), pp. 314-317, 2004.

19. B. Yegnanarayana, K. s. Anil, B. V. K. V. Kumar, and M. Savvides., Determination of pose angle of face using dynamic space warping., International Conference on Information Technology: Coding and Computing, vol.1, pp. 661-664, 2004.

20. L. Chen, L. Zhang, Y. Hu, M. Li, and H. Zhang, Head pose estimation using Fisher Manifold learning., IEEE International Workshop on Analysis and Modeling of Faces and Gestures, pp. 203-207, 2003.

21. S. Joun, H. Kim, Y. Chung and D. Ahn, An Experimental Study on Measuring Image Quality of Infant Fingerprints., Proc. of Knowledge-Based Intelligent Information and Engineering Systems, Part II, pp. 1261-1269, September 3-5, 2003.

22. T. J. Chen, K. S. Chuang, J. Wu, S. C. Chen, I. M. Hwang, and M. L. Jan., Blind quality assessment of JPEG2000 compressed images using natural scene statistics., Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers, vol. 2 , pp. 1403-1407, 2003.

23. K. Wang, Y. Wang, B. Yin, and D. Kong., Face pose estimation with a knowledge-based model., Proceedings of the 2003 International Conference on Neural Networks and Signal Processing, pp. 1131-1134, 2003

24. E. Lim, X. Jiang, and W. Yau., Fingerprint quality and validity analysis., IEEE International Conference on Image Processing (ICIP), Vol 1. pp 469-472, September 2002.

25. M. Y. Yao, S. Pankanti, N. Haas, N. K. Ratha and R. M. Bolle., Quantifying Quality: A Case Study in Fingerprints., Proc. of IEEE on Automatic Identification Advanced Technologies (AutoID), pp.126-131, March 2002.

26. L. L. Shen, A. Kot and W.M Koo., Quality measures of fingerprint images., Proc. of the Third AVBPA 2001, p182-271, June 2001.

27. N. K. Ratha and R. M. Bolle., Fingerprint image quality estimation., IBM computer science research report RC21622, 1999.,

28. R. Bolle et al., System and methods for determining the quality of fingerprint images., United States patent number US596356, 1999.,

29. J. Huang, X. Shao, and H. Wechsler., Face pose discrimination using support vector machines (SVM)., Proc. Fourteenth International Conference on Pattern Recognition, pp. 154-156, May 1998.

30. L. Hong, Y. Wan and A.K. Jain., Fingerprint image enhancement: algorithm and performance evaluation., IEEE transaction on pattern analysis and machine intelligence, vol. 20, no.8, August 1998.

31. K. Hattori, S. Matsumori, and Y. Sato., Estimating pose of human face based on symmetry plane using range and intensity images., Proc. Fourteenth International Conference on Pattern Recognition, pp. 1183-1187, 1998.

32. N. B. Nill and B. H. Bouzas., Objective Image Quality Measure Derived from Image Power Spectra., Optical Enginering, Vol. 31 no. 4 pp. 813-825, April 1992.

Performance Testing

1. P. Grother and E. Tabassi., Performance of biometric quality measures. ,IEEE Transaction on Pattern Analysis and Machine Intelligence (PAMI), vol. 29, pp. 531-543, APril 2007.

2. F. Alonso-Fernandez, J. Fierrez-Aguilar, and J. Ortega-Garcia., A review of schemes for fingerprint image quality computation., In COST 275 - Biometrics based recognition of people over the internet, October 2005.

3. A. J. Mansfield, editor., ISO/IEC 19795-1 Biometric Performance Testing and Reporting: Principles and Framework., JTC1 / SC37 / Working Group 5, FDIS, August 2005.

4. M. Thieme, editor., ISO/IEC 19795-2 Biometric Performance Testing and Reporting: Scenario Testing., JTC1 /SC37 / Working Group 5, CD2, August 2005.

5. N. B. Nill., Test Procedures For Verifying IAFIS Image Quality Requiments for Fingeprint Scanners and printers., Mitre Technical Report (MTR 05B0000016), April 2005.

6. J. Fierrez-Aguilar, D. Simon-Zorita, J. Ortega-Garcia and J. Gonzalez-Rodriguez., Image quality and position variability assessment in minutiae-based fingerprint verification., IEE Proceedings on Vision, Image and Signal Processing, 150(6):395–401, December 2003. Special Issue on Biometrics on the Internet.,

7. J. Moon and H. Kim Study on Metrics for Fingerprint Image Quality Technical Report, Dept. of Information and Communication Engineering, Inha University, Incheon, Korea.,

8. N. Sickler et al., Image Quality and the Elderly Biometric Standards, Performance, and Assurance Laboratory, Purdue University.,

Standardization

1. D. Benini et al., Report of the Ad Hoc Group on Biometric Quality: Document N1128. ISO/IEC, JTC1 / SC37 / Working Group 3, May 2005.  http://isotc.iso.org,

2. ISO/IEC JTC1 / SC37 / Working Group 3. ISO/IEC 19794 Biometric Data Interchange Formats, 2005.

3. C. J. Tilton et al., The BioAPI Specification, INCITS 358. American National Standards Institute, Inc., 2002.

4. F. L. Podio et al., Common Biometric Exchange Formats Framework (CBEFF) INCITS 398-2005, American National Standard for Information Technology

Reference Data

1. J. Fierrez, J. Ortega-Garcia, D. Torre-Toledano, and J. Gonzalez-Rodriguez., BioSec baseline corpus: A multimodal biometric database., Pattern Recognition, Vol. 40, n. 4, pp. 1389-1392, April 2007.

2. National Institute of Standards and Technology, Fingerprint Databases

3. University of Zagreb, List of Face Recognition R+D Databases

4. J. Ortega-Garcia, J. Fierrez-Aguilar, D. Simon, J. Gonzalez, M. Faundez-Zanuy, V. Espinosa, A. Satue, I. Hernaez, J.-J. Igarza, C. Vivaracho, D. Escudero and Q.-I. Moro., MCYT baseline corpus: A Bimodal Biometric Database Proceedings of the IEE Conference on VISP. Vol 150, No. 6, pp. 395-401, December 2003.

Non-Biometric Quality

1. Z. Liu and R. Laganiere., Phase congruence measurement for image similarity assessment., Pattern Recognition Letters, vol. 28, no. 1, pp. 166-172, Jan.2007.

2. P. Gastaldo and R. Zunino., Neural networks for the no-reference assessment of perceived quality., Journal of Electronic Imaging, vol. 14, no. 3, pp 772-775, 2005.

3. Z. Guangtao, Z. Wenjun, Y. Xiaokang, and X. Yi., Image quality assessment metrics based on multi-scale edge presentation., IEEE Workshop on Signal Processing Systems Design and Implementation, pp. 331-336, 2005.

4. H. R. Sheikh, A. C. Bovik, and L. Cormack., Quality degradation in lossy wavelet image compression., Journal of Digital Imaging, vol. 16, no. 2, pp. 210-215, June 2003.

5. Z. Wang, H. R. Sheikh, and A. C. Bovik., No-reference perceptual quality assessment of JPEG compressed images., Proc. International Conference on Image Processing, I-477- I-480, 2002.

6. L. Xin., Blind image quality assessment., Proc. International Conference on Image Processing, p. I-449-I-452, 2002.

7. Z. Zhang and R. S. Blum, On estimating the quality of noisy images., Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 2897-2900, 1998.

8. Peter Kovesi., Symmetry and Asymmetry From Local Phase., AI'97, Tenth Australian Joint Conference on Artificial Intelligence. 2 - 4 December 1997.

9. D. M. Levi and S. A. Klein., Weber law for position - the role of spatial-frequency and contrast., Vision Research, 32:(12) 2235-2250, Dec. 1992

Biometric Quality Links

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