Signature Recognition using Cluster Based Global Features
Hemant B. Kekre, Vinayak Ashok Bharadi · 2009
In this paper we discuss an off-line signature recognition system designed using clustering techniques. These cluster based features are mainly morphological feature, they include Walsh coefficients of pixel distributions, vector quantization based codeword histogram, grid & texture information features and geometric centers of a signature. In this paper we discuss the extraction and performance analysis of these features. We present the FAR, FRR achieved by the system using these features . We compare individual performance and overall system performance.