Fraudulence Detection Using Image Processing Approach
Sanchita S. Mendhe, Varsha R. Ratnaparkhe · 2018
The modification made in cheques, wills, contracts and other valuable information on paper documents leads to the fastest growing crimes as well as serious financial impairment. The uprising graphical record of such crimes leads to a great loss. However, it is most challenging to identify if the modification is made with the same color pen. In this paper proposed a structure for recognition of such modifications in ballpoint pen strokes using radiation diagram recognition technique. For this, a set of features are extracted by Gray Level Co-occurrent matrix (GLCM), Legendre Moments and Geometric Moments based on texture. Finally for the identification of modification the KNN and SVM classifiers are used. Keywords: texture features, KNN, SVM classifier.