Model-Based Approach for Compression of Fingerprint Images


We propose a new fingerprint image compression scheme based on the hybrid model of image. Our scheme uses the essential steps of a typical automated fingerprint identification system (AFIS) such as enhancement, binarization and thinning to encode fingerprint images. The decoding process is based on reconstructing a hybrid surface by using the gray values on ridges and valleys. In this compression scheme, the ridge skeleton is coded efficiently by using differential chain codes. Valley skeleton is derived from ridge skeleton and the gray values along the ridge and valley skeletons are encoded using discrete cosine transform. The error between original and replica is also encoded to increase quality. One advantage of our approach is that original features such as end points and bifurcation points can be extracted directly from compressed image even for a very high compression ratio. Another advantage is that the proposed scheme can be integrated to a typical AFIS easily. The algorithm has been applied to various fingerprint images, and high compression ratios like 63:1 have been obtained. A comparison to Wavelet/Scalar Quantization (WSQ) has been also made.


Computer Science

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Article - Conference proceedings

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Publication Date

01 Dec 1999

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