Abstract

Maintaining the attendance database of thousands of students has become a tedious task in the universities in Sri Lanka This paper comprises of 3 phases signature extraction signature recognition and signature verification to automate the process We applied necessary image processing techniques and extracted useful features from each signature Support Vector Machine SVM multiclass Support Vector Machine and Kolmogorov Smirnov test is used to signature classification recognition and verification respectively The described method in this report represents an effective and accurate approach to automatic signature recognition and verification It is capable of matching classifying and verifying the test signatures with the database of 83 33 100 and 100 accuracy respectively