Off-Line Persian Signature Identification and Verification Based on Image Registration and Fusion

Abstract

Signature verification and Identification has great importance for authentication purpose. Persian signatures are different from other signature types because people usually do not use text in it and they draw a shape as their signature, therefore, a different approach should be considered to process such signatures. In this paper, a method for off-line Persian signature identification and verification is proposed that is based on Image Registration, DWT (Discrete Wavelet Transform) and Image Fusion. Training signatures of each person are registered to overcome shift and scale problem. To extract features, at first, DWT is used to access details of signature; then several registered instances of each person signatures are fused together to generate reference pattern of person's signatures. In the classification phase, Euclidean distance between the test image and each pattern is used in different sub-bands. Experimental results confirmed the effectiveness of the proposed method. However, the proposed method has been tested on Persian signature database but we believe it can be extended for other languages.