Handwritten Signature Recognition System Using Euler Number
Souvik Chatterjee, Joydeep Mukherjee · 2014
Abstract: This paper reports the design, implementation, and evaluation of a research work for developing an digital handwritten signature identification system using binary image analysis. The developed signature identification system mainly used binary image analysis provided by MATLAB environment. In order to train and test the developed signature identification system, an in-house hand signatures database is created, which contains hand signatures of 5 persons (2 males and 3 females) each of which is repeated 10 times. Therefore, a total of 50 hand signatures are collected. The collected hand signatures have gone through pre-processing steps such as producing a digitized version of the signatures using a scanner, converting input images type to a standard binary images type, cropping, normalizing images size, and reshaping in order to produce a ready-to-use hand signatures database for training and testing the signature identification system. Feature such as EULER NUMBER is then selected to be used in the system, which reflects information about the structure of the hand signature image. Overall, the handwritten signatures based system obtained an average recognition rate of 80 % for all persons.