A Fast Fingerprint Image Alignment Algorithms Using K-Means and Fuzzy C-Means Clustering Based Image Rotation Technique

The Fingerprint recognition system involves several steps. In such recognition systems, the orientation of the fingerprint image has influence on fingerprint image enhancement phase, minutia detection phase and minutia matching phase of the system. The fingerprint image rotation, translation, and registration are the commonly used techniques, to minimize the error in all these stages of fingerprint recognition. Generally, image-processing techniques such as rotation, translation and registration will consume more time and hence impact the overall performance of the system. In this work, we proposed fuzzy c-means and k-mean clustering based fingerprint image rotation algorithm to improve the performance of the fingerprint recognition system. This rotation algorithm can be applied as a pre-processing step before minutia detection and minutia matching phase of the system. Hence, the result will be better detection of minutia as well as better matching with improved performance in terms of time.