Abstract
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Article Information:
Research on Lossless Compression Algorithms of Low Resolution Palmprint Images
Hengjian Li, Lianhai Wang, Song Zhao and Zutao Zhang
Corresponding Author: Hengjian Li
Submitted: December 27, 2011
Accepted: January 16, 2012
Published: July 15, 2012 |
Abstract:
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In this study, lossless grayscale image compression methods are compared on public palmprint image
databases. Effect of lossy compression algorithms on biometric samples has been well studied. However,
lossless compression algorithms on the compression ratios have little been appreciated. In this study, we review
and the stateofart lossless compression algorithms and investigate the performance using different when
processing palmprint sample data. In particular, including those based on transformation (integer transform
based in the JPEG , JPEG2000 and JPEG XR system, as well as the SPbased transform coding method), based
on predictive lossless compression algorithms (LJPEG, CALIC and JPEGLS), dictionarybased compression
methods (PNG UHA,7z and RAR). To gain a better and reliable result, these lossless compression algorithms
are employed to test on different palmprint databases. Based on the testing results using an open palmprint
image database, analysis and comparison, CALIC gives high compression ratios in a reasonable time, whereas
JPEGLS is nearly as effective and very fast. The performance shows that a guide is given to choose which
lossless palmprint image compression algorithm. At last, to find better solutions on how to improve lossless
compression performance, we give some examples and suggestions.
Key words: Biometric traits, comparison efficiency, lossless image compression, palmprint image, , ,
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Abstract
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Cite this Reference:
Hengjian Li, Lianhai Wang, Song Zhao and Zutao Zhang, . Research on Lossless Compression Algorithms of Low Resolution Palmprint Images. Research Journal of Applied Sciences, Engineering and Technology, (14): 2072-2081.
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![](http://www.maxwellsci.com/images/RJASET-maxw.jpg) |
ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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