Abstract: Based on mechanism of human visual attention, five features are chosen in this paper to simulate the process of subjective quality assessment of fingerprint images. Among these features, two of them are extracted by two proposed methods, a minutiae reliability assessment method based on Polar Coordinates Centrum Sensitivity (PCCS) and a gray-scale image contrast based on Otsu algorithm. Experimental results show that this feature set on both Error Back Propagation (BP) Neural Network and Support Vector Machine (SVM) gives high classification accuracy.

Key words: Information Processing Technology, Fingerprint Image Quality Assessment, Mechanism of Visual Attention, Minutiae Reliability Assessment, Gray Level Image Contrast Assessment