Offline signature verification based on ASIFT

A novel offline signature verification method based on the affine and scale invariant feature transform (ASIFT) was proposed by analyzing the existing local invariant features and the property of the disguised signature. The method consists of the following steps, the preprocessing including image graying and resizing was performed on the signature images; the key points were detected and the corresponding descriptors were extracted from the processed images; the descriptors extracted from the query and reference images were matched and the random sample consensus (RANSAC) algorithm was used to refine the matched result. Then the average distance was computed according to the distances between the descriptors of the correct matched points. The verification decision was given by comparing the average distance and the number of the correct matched points with the thresholds. The proposed method was evaluated on a public signature dataset including the disguised signatures and the experimental results show that the proposed method outperforms the state-of-the-art algorithms with reducing the equal error rate (EER) by 5%.