Fingerprint recognition remains as one of the most prominent biometric identification methods. The quality of the fingerprint image is the most significant factor in a reliable matching process. Any preprocessing algorithm should aim to enhance the quality of the existing features without creating false features. In this paper we describe a regional average thresholding (RAT) scheme for 256 grey scale images. The algorithm thresholds by moving a small, fixed size window on 256 colour grey scale image and uses a novel averaging scheme. The thresholded image is then operated on by a median filtering (3×3 mask or 5×5 mask) algorithm which eliminates any random noise contained in a thresholded fingerprint image. The filtered image is finally operated on by a ridge following thinning algorithm. We compare the results of using this algorithm on median filtered and nonfiltered images.
Pre-processing of fingerprint images
1997-01-01
5 pages
Article (Journal)
English
regional average thresholding , thinning algorithm , grey scale images , random noise , fingerprint recognition , biometric identification methods , fingerprint image preprocessing , image enhancement , median filtering , colour grey scale image , fingerprint identification , image matching , image colour analysis , features , averaging scheme
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