Off-line Signature Verification Based on High Pressure Polar Distribution

Features representing information of High Pressure Points from a static image of a handwritten signature are analyzed for an offline verification system. From grayscale images, a new approach for High Pressure threshold estimation is proposed. Two images, one containing the High Pressure Points extracted and other with a binary version of the original signature, are transformed to polar coordinates where a pixel density ratio between them is calculated. Polar space had been divided into angular and radial segments, which permit a local analysis of the high pressure distribution. Finally two vectors containing the density distribution ratio are calculated for nearest and farthest points from geometric center of the original signature image. Experiments were carried out using a database containing signature from 160 individual. The robustness of the analyzed system for simple forgeries is tested out with KNN and PNN standard models. For the sake of completeness, a comparison of the results obtained by the proposed approach with similar works published is presented.