A Novel Hybrid Gabor Filter Based On Automatic Wavelet Selection with Application to Fingerprint Enhancement

Abstract

For decades, Image enhancement techniques have been pushing the envelope of image processing applications. The aim of image enhancement is to recover the information perception contained in the image for human eyes besides delivering the best input for image processing systems. Fingerprint system is one of the most popular image processing system, The performance of any fingerprint system highly depends on the fingerprint image quality; therefore, fingerprint image enhancement is an essential stage in fingerprint systems. Gabor filtering has been widely used to facilitate various fingerprint applications. Meanwhile, enhancement using Gabor filter still has several drawbacks. In the present enhancement approach, we propose an active hybrid contextual module used for image enhancement. In order to prove the efficiency and effectiveness the proposed algorithm applied to fingerprint image. The proposed filter methodology includes eight stages, each one designed for a particular image defect, which can much improve the clarity and continuity of ridge structures, link broken ridges and reduce the false minutia. The experimental results show that the enhanced image quality by using our algorithm has higher performance, robustness and versatility. Presented approach might be useful for many applications related to digital image processing, computer vision.