In today’s’ world forgery of signature is very widely increased. There are many sophisticated scientific techniques to identify a correct signature. As signatures are widely accepted bio-metric for authentication and identification of a person because every person has a distinct signature with its specific behavioural property, so it is very much necessary to prove the authenticity of signature itself.A huge increase in forgery cases relative to signatures induced a need of Signature recognition system.However human signatures can be handled as an image and recognized using computer vision and neural network techniques. In this paper we have taken a set of trained images and stored their features in a database and to test an unknown image we compare the features and calculating the matching factors. We have considered 70 % as threshold for human signature recognition. Regarding creation of recognizer we gave considered HARRIS and SUFR Features. efficient “Signature Verification System”.

Image Processing, Pattern Recxognition,Feature Selection,HARRIS,SURF

[1] A Bansal, B Gupta, G Khandelwal,S Chakraverty “Offline Signature Verification Using Critical Region Matching” International Journal of Signal Processing, Image Processing and Pattern Vol. 2, No. 1, 2009
[2] A. Masood and M. Sarfraz. “Corner detection by sliding rectangles along planar curves” ,Computers & Graphics, Vol. 31, pp.440-448, 2007. [3] A K Das, A Massand ,S Patil “A novel proxy signature scheme based on user hierarchical access control policy” Journal of king Saud University- Computer and Information Sciences, 2013
[4] A Pansare and S Bhatia “Handwritten Signature Verification Using Neural Network” International Journal of Applied Information Systems (IJAIS), Vol. 1, No. 2, 2012
[5] S. Harpreet, “Robust Video Watermarking Algorithm Using K_Harries Feature Point Detection”, International Journal of Soft Computing and Engineering (IJSCE), ISSN: 2231-2307, Volume-5 Issue-4, September 2015..
[6]S Garhawal and N Shukla “SURF Based Design and Implementation for Handwritten Signature Verification” International Journal of Advanced esearch in Computer Science and Software ngineering (IJARCSSE), Vol. 3, Issue 8, 2013
[7].D.Mitra,R.Barik,S.Roy,S.Bhattacharyya“A Survey on Image Segmentation and Image Registration” ,ACEEE-CPS, International Conference on Computing,Communication & Manufacturing, ISBN: 978-0-9940194-0-0,Pages 61-69
[8]D.Mitra,R.Barik,S.Roy,S.Bhattacharyya“Cumulative Measurement of Image Entropy on Different Mathematical Morphological Operation”,ACEEE-CPS, International Conference on Computing,Communication & Manufacturing, ISBN: 978-0-9940194-0-0,Pages 35-39
[9] D Mitra, K G Verma “Information Processing using Multilevel Masking to Image Segmentation “ , International Journal of Computer Applications , pp 1-6.
[10] S Gupta , K G Verma, D Mitra “Identification Of Mass Of Tissue Growth In Brain Region Under The Framework Of Image Segmentation(http://dx.doi.org/10.21172/1.84.28 )” , International Journal of Latest Trends in Engineering and Technology .pp 179-186, Volume 8 Issue 4 - July 2017
[11] P Metri, AKaur “Handwritten Signature Verification using Instance Based Learning” ,International Journal of Computer Trends and Technology- March to April Issue 2011 ,Pune,India
[12] D Bhattacharyya, and T Kim “Design of Artificial Neural Network for Handwritten Signature Recognition” International Journal Of Computers And Communications Issue 3, Volume 4, 2010
[13] Gonzalez, Woods “Digital Image Processing”
[14] Sanjay Sharma “Fundamental Of Digital Image Processing”
[15] Stuart Russel & Peter Norvig “Artificial Intelligence: A Modern Approach”, Pearson, 2009
[16] kevin P. Murphy “Machine Learning: A probabilistic perspective”