Fingerprint Image Enhancement Method based on Adaptive Median Filter

Abstract

The traditional median filtering method uses a fixed filter window size method to remove the impulse noise in a fingerprint image. If the filtering window size is small, the traditional median filtering method will not filter out the impulse noise completely. If the filtering window size is large, the fingerprint image may become blurred. To solve the problem, a method based on adaptive median filter is proposed for fingerprint image enhancement processing and impulse noise removal in the paper. The use of adaptive median filtering to remove the impulse noise of the fingerprint image mainly involves three steps. First, the size of the adaptive median filter window is initialized, and it is judged whether the center pixel of the filter window in the fingerprint image is impulse noise. Second, the size of the filter window is determined based on the median value, the maximum value, and the minimum value within the filter window. Finally, median filtering is performed on the fingerprint image under the filter window size obtained in the previous steps, and the filter output value is used instead of the window center pixel value. The method is tested on rolled fingerprint images contaminated by impulse noise and fingerprint images contaminated by impulse noise from a crime scene. Experimental results show that the method based on adaptive median filter for fingerprint image enhancement outperforms the traditional median filtering method in filtering impulse noise performance.