We propose a new fingerprint image compression scheme based on the hybrid model of an 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. The valley skeleton is derived from the ridge skeleton and the gray values along the ridge and valley skeletons are encoded using the discrete cosine transform. The error between the original and the replica is also encoded to increase the 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.

Meeting Name

1999 International Conference on Image Processing, 1999


Computer Science

Keywords and Phrases

Automated Fingerprint Identification System; Bifurcation Points; Data Compression; Decoding Process; Differential Chain Codes; Discrete Cosine Transform; Discrete Cosine Transforms; End Points; Feature Extraction; Fingerprint Identification; Fingerprint Image Compression; Gray Values; High Compression Ratio; Hybrid Model; Hybrid Surface Reconstruction; Image Coding; Image Enhancement; Image Reconstruction; Image Thinning; Model-Based Approach; Ridge Skeleton; Transform Coding; Valley Skeleton; Wavelet/Scalar Quantization

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type





© 1999 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Full Text Link