H. B. Kekre
ABSTRACT
Dynamic signature is an important behavior based biometric. Dynamic features of human signature are available in case of on line signatures. Spatial Co-ordinates, pressure, azimuth, altitude variation w. r. t. time is analyzed in this paper. The signature feature vector is extracted from the captured feature points using transforms such as DCT, FFT, WHT & kekre's Transform. Derived features such as Velocity, Acceleration, velocity & Acceleration angle as well as Row & Column mean of pressure is used for analysis. Finally the performance is compared for above mentioned variations.
- A. K. Jain, A. Ross, S. Prabhakar, "An Introduction to Biometric Recognition", IEEE Transactions on Circuits and Systems for Video Technology, Vol. 14, No. 1, January 2004 Google Scholar
Digital Library
- A. K. Jain, A. Ross, and S. Prabhakar, "On Line Signature Verification", Pattern Recognition, vol. 35, no. 12, Dec 2002. pp. 2963--2972Google ScholarCross Ref
- http://sourceforge.net/projects/vbtablet/Google Scholar
- H. B. Kekre, V A Bharadi, "Using Component Object Model for Interfacing Biometrics Sensors to Capture Multidimensional Features", IJJCCT 2009, China, Dec 2009Google Scholar
- H. B. Kekre, V A Bharadi, "Dynamic Signature Preprocessing by Modified Digital Difference Analyzer Algorithm", ThinkQuest 2010, Mumbai, India, March 2010Google Scholar
- H. B. Kekre, A. Athawale, D. Sadavarti, "Algorithm To Generate Kekre's Wavelet Transform from Kekre's Transform", IJSET, June 2010 (In Press)Google Scholar
- H B Kekre, T K Sarode, V A Bharadi, A A Agrawal, R J Arora, M C Nair, "Performance Comparison of Full 2-D DCT, 2-D Walsh and 1-D Transform over Row Mean and Column Mean for Iris Recognition", Proceedings of ACM International Conference ICWET 2010, India, Feb 2010 Google ScholarDigital Library
Index Terms
- Performance comparison of DCT, FFT, WHT & Kekre's transform for on-line signature recognition
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