Writer-independent Handwritten Signature Verification based on One-Class SVM classifier

The limited number of writers and the lack of forgeries as counterexample to construct the systems is the main difficulty task for designing a robust off-line Handwritten Signature Verification System (HSVS). In this paper, we propose to study the influence of writer´s number using conjointly the curvelet transform and the One-Class Support Vector Machine (OC-SVM), which takes in consideration only genuine signatures. The design of the HSVS is based on the writer-independent approach. Experimental results conducted on the standard CEDAR and GPDS datasets demonstrate that the proposed method allows achieving the lowest Average Error Rate with a limited number of writers.