Abstract
A new compression algorithm for fingerprint images is introduced. Using Lattice Vector Quantization (LVQ), a technique for determining the largest radius of the Lattice and its scaling factor is presented. The design is based on obtaining the smallest possible Expected Total Distortion (ETD) measure, using a given bit budget, while using the smallest codebook size. In the proposed Piecewise-Uniform Pyramid LVQ, the wedge problem encountered with the Pyramidal Lattice point shells is resolved. At very low bit rates, for the coefficients with high-frequency content, the Positive-Negative Mean (PNM) method is proposed to improve the resolution of the reconstructed image. The proposed algorithm results in a high compression ratio and a high reconstructed image quality with a low computational load compared to other existing algorithms.
| Original language | English |
|---|---|
| Pages (from-to) | 3117-3120 |
| Number of pages | 4 |
| Journal | Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing |
| Volume | 4 |
| State | Published - 1997 |
| Externally published | Yes |
| Event | Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 5) - Munich, Ger Duration: 21 Apr 1997 → 24 Apr 1997 |
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