NDLI: Evolutionary optimization of JPEG quantization tables for compressing iris polar images in iris recognition systems

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Evolutionary optimization of JPEG quantization tables for compressing iris polar images in iris recognition systems

Content Provider	Semantic Scholar
Author	Konrad, Mario Stogner, Herbert Uhl, Andreas
Copyright Year	2009
Abstract	Recognition performance in iris biometrics strongly depends on the image quality. The appliance of compression algorithms to iris images raises the question whether it is possible to adapt those algorithms for biometrical purposes. In this work, we propose customized JPEG quantization matrices for compressing iris polar images to positively impact the recognition performance. We build on previous research and apply a genetic algorithm to obtain specialized matrices for destined compression ratios. The proposed tables are able to clearly outperform JPEG's standard quantization matrix. Moreover, some matrices also provide superior results in terms of ROC characteristics as compared to the reference scenario using uncompressed images. This leads to clearly lower error rates while also significantly reducing the necessary amount of data storage and transmission.
Starting Page	534
Ending Page	539
Page Count	6
File Format	PDF HTM / HTML
DOI	10.1109/ISPA.2009.5297685
Alternate Webpage(s)	http://www.cosy.sbg.ac.at/~uhl/Evolutionary_ispa.pdf
Alternate Webpage(s)	https://doi.org/10.1109/ISPA.2009.5297685
Journal	2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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