Most of the current security and attendance systems are shifting towards automated biometric systems, the most popular biometrics being fingerprints. In Automated Fingerprint Identification Systems (AFIS), the fingerprint of an individual needs to be identified with that stored in the database. In this paper, a method which deals with fingerprint identification in the transform domain is considered and the main focus is on the reduction of the processing time. First, the mean of rows (or columns) of the fingerprint image is computed, this converts a two dimensional image signal into one dimension. The one- dimensional Walsh transform of the row (or column) vector is generated and is distributed in a complex plane which is subjected to sectorization to generate the feature vector. The feature vector of a given test image is compared to those present in the database. The scores from row and column transform methods are fused using OR and MAX functions. The results with accuracy of more than 73% (for 16 sectors) and high computational speed show that the method can be used in fingerprint identification in application with requirements of less processing time.

1. D. Maltoni, D. Maio, A. Jain, and S. Prabhakar: Handbook of Fingerprint Recognition. New York, Springer (2003)
2. Anil Jain et al.: Intelligent Biometric Techniques in Fingerprint and Face Recognition, CRC Press (1999)
3. Gonzalez Rafael C., Woods Richard E.: Digital Image Processing. 3rd edition. Prentice Hall (2008)
4. L.Hong, Y.Wan and A.K.Jain: Fingerprint Image Enhancement :Algorithm and Performance Evaluation. IEEE Transaction on Pattern Analysis and Machine Intelligence, voI.20.no.8,Aug (1998)
5. X. Jang and W.Y. Yau: Fingerprint Minutiae matching based on the local and global Structures. In: IEEE 15th Int. Conf. on Pattern Recognition, Vol.2, pp.1024--1045 (2000)
6. H. B. Kekre, Tanuja K. Sarode, Vinaya M. Rawool: Fingerprint Identification using Discrete Sine Transform (DST). In: International Conference on Advanced Computing & Communication Technology (ICACCT-2008) Asia Pacific Institute of Information Technology, Panipat, India (2008)
7. H. B. Kekre, Tanuja K. Sarode, Vinaya M. Rawool: Fingerprint Identification using Principle Component Analysis (PCA). In: International Conference on Computer Networks and Security (ICCNS08), Pune (2008)
8. H. B. Kekre, Tanuja K. Sarode , Sudeep D. Thepade: DCT Applied to Column Mean and Row Mean Vectors of Image for Fingerprint Identification. In: International Conference on Computer Networks and Security (ICCNS08), Pune (2008)
9. Anil Jain, Arun Ross, Salil Prabhakar: Fingerprint matching using minutiae and texture features. In: Int’l conference on Image Processing (ICIP), pp. 282--285 (2001)
10. Walsh, J. L.: A Closed Set of Normal Orthogonal Functions. Amer. J. Math. , 5--24 (1923)
11. John Berry and David A. Stoney: The history and development of fingerprinting, Advances in Fingerprint Technology, Henry C. Lee and R. E. Gaensslen, Eds., pp. 1--40. CRC Press Florida, 2nd edition (2001)
12. Arun Ross, Anil Jain, James Reisman: A hybrid fingerprint matcher. In: Int’l conference on Pattern Recognition (ICPR) (2002)
13. H.B.Kekre, Dhirendra Mishra: Four Walsh Transform Sectors Feature Vectors for Image Retrieval from Image Databases. International Journal of Computer Science and Information Technology (IJCSIT) Vol. 01, No. 02 (2010)
14. H.B. Kekre, Tanuja K. Sarode, Rekha Vig : Fingerprint Identification using Sectorized Cepstrum Complex Plane. International Journal of Computer Applications (IJCA) Volume 8– No.1, October (2010)
15. H. B. Kekre, Tanuja K. Sarode, Rekha Vig, “Fingerprint Identification using Sectionized Walsh Transform of Row and Column Mean” in International Conference on Advances in Computing, Communication and Controls, January 2011
16. H. B. Kekre, Tanuja K. Sarode, Rekha Vig, “Fingerprint Matching using Sectorized Complex Walsh Plane in Transform Domain” in International Conference and Workshop in Emerging Trends, February 2011

Fingerprint identification Walsh transform row and column mean vector sectorization complex plane