Offline signature identification and verification using noniterative shape context algorithm

The paper presents experimental results on offline signature identification and verification. At the first stage of the presented system, the binary image of the signature undergoes skeletonization process using KMM algorithm to have a thinned, one pixel-wide line, to which a further reduction is applied. For each thinned signature image a fixed number of points comprising the skeleton line are selected. The recognition process is based on comparing the reference signatures with the questioned samples using distance measure computed by means of Shape Context algorithm. The experiments were carried out using a database containing signatures of 20 individuals. For the verification process random forgeries were used to asses the system error. The main advantage of the presented approach lies in utilizing only one reference signature for both identification and verification tasks, whereas the achieved results are comparable with respect to the systems that use several training samples per subject.