FCM-based orientation selection for competitive coding-based palmprint recognition
Coding based methods are among the most promising palmprint recognition methods. As one representative coding method, the competitive code first convolves the palmprint image with a bank of Gabor filters with different orientations and then encodes the dominant orientation into its bitwise representation. Despite its effectiveness, few investigations have been given to study the influence of the number of filters and the orientation of each filter. In this paper, based on the statistical orientation distribution and the orientation separation principle, we propose a modified fuzzy C-means cluster algorithm to determine the orientations of filters. Experimental results indicate that, the proposed method achieves higher verification accuracy while compared with that of the original competitive code and several state-of-the-art methods. Considering both the computational complexity and the verification accuracy, six filters would be the optimal choice for proposed method.