Fingerprint compression using a modified wavelet transform and pyramid lattice vector quantization

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Fingerprint compression using a modified wavelet transform and pyramid lattice vector quantization

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dc.contributor.author Kasaei, S
dc.contributor.author Deriche, M
dc.contributor.author Boashash, B
dc.date.accessioned 2011-09-28T19:03:20Z
dc.date.available 2011-09-28T19:03:20Z
dc.date.issued 1996-11
dc.identifier.citation TENCON '96. Proceedings. 1996 IEEE TENCON. Digital Signal Processing Applications Issue Date : 26-29 Nov 1996 Volume : 2 On page(s): 798 en_US
dc.identifier.isbn 0-7803-3679-8
dc.identifier.uri http://hdl.handle.net/10576/10751
dc.description This paper presents a new compression algorithm for fingerprint images. The algorithm is introduced, using a modified wavelet packet scheme which uses a fixed decomposition structure, designed for fingerprint images, in order to decorrelate the image pixels. (The most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated). en_US
dc.description.abstract A new compression algorithm for fingerprint images is introduced. A modified wavelet packet scheme which uses a fixed decomposition structure, matched to the statistics of fingerprint images, is presented. A technique for determining the most important coefficients is introduced. The algorithm uses both hard and soft thresholding schemes to make the procedure fast and efficient. The bit allocation for each subimage of the modified coefficients is determined. Each subimage uses a different quantization technique based on its entropy. Then, a lossless compression technique, Huffman, is used to obtain further compression. The algorithm results in a high compression ratio and a high reconstructed image quality with a low computational cost, compared to other existing algorithms. The performance of the proposed algorithm is compared to that of other decomposition techniques: ordinary wavelet transform (OWT), entropy-based best basis selection (E-BBB), wavelet/scalar quantization (WSQ) and JPEG. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject Huffman loss-less compression en_US
dc.subject JPEG en_US
dc.subject algorithm performance en_US
dc.subject coefficients en_US
dc.subject compression algorithm en_US
dc.subject decomposition techniques en_US
dc.subject entropy-based best basis selection en_US
dc.subject fingerprint compression en_US
dc.subject fingerprint images en_US
dc.subject fixed decomposition structure en_US
dc.subject hard thresholding en_US
dc.subject high compression ratio en_US
dc.subject image statistics en_US
dc.subject low computational cost en_US
dc.subject modified wavelet packet scheme en_US
dc.subject modified wavelet transform en_US
dc.subject ordinary wavelet transform en_US
dc.subject pyramid lattice vector quantization en_US
dc.subject reconstructed image quality en_US
dc.subject soft thresholding en_US
dc.subject sub-image en_US
dc.subject wavelet/scalar quantization en_US
dc.title Fingerprint compression using a modified wavelet transform and pyramid lattice vector quantization en_US
dc.type Article en_US

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