A Preprocessing Algorithm for Touchless Fingerprint Images

Abstract

Touchless fingerprint recognition with high acceptance, high security, hygiene advantages, is currently a hot research field of biometrics. The background areas of touchless fingerprints are more complex than those of the contact: the touchless fingerprint image will appear rotation and translation phenomenon, what’s more, the contrast of the ridge and valley lines is much lower. These factors seriously affected the performance of the touchless fingerprint recognition. So the general methods for contact fingerprint images are difficult to achieve a good effect. A novel method is proposed to preprocess the images reasonably aiming at these features of touchless fingerprint images. Firstly, the Otsu based on the Cb component of the YCbCr model is adopted to extract the finger area. Secondly, we combined the high-frequency enhancement filter with the iterative adaptive histogram equalization technique to enhance fingerprint images. Thirdly, we proposed a new method to extract the ROI fingerprint area. Lastly, the AR–LBP algorithm is adopted for feature extraction and the nearest neighbor classifier is used for feature matching. Experimental results show that the proposed method can achieve excellent image identify results.