Paper
11 January 2005 Using optical wavelet packet transform to improve the performance of an optoelectronic iris recognition system
De Cai, Qiaofeng Tan, Yingbai Yan, Guofan Jin, Qingsheng He
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Abstract
Iris, one important biometric feature, has unique advantages: it has complex texture and is almost unchanged for the lifespan. So iris recognition has been widely studied for intelligent personal identification. Most of researchers use wavelets as iris feature extractor. And their systems obtain high accuracy. But wavelet transform is time consuming, so the problem is to enhance the useful information but still keep high processing speed. This is the reason we propose an opto-electronic system for iris recognition because of high parallelism of optics. In this system, we use eigen-images generated corresponding to optimally chosen wavelet packets to compress the iris image bank. After optical correlation between eigen-images and input, the statistic features are extracted. Simulation shows that wavelet packets preprocessing of the input images results in higher identification rate. And this preprocessing can be fulfilled by optical wavelet packet transform (OWPT), a new optical transform introduced by us. To generate the approximations of 2-D wavelet packet basis functions for implementing OWPT, mother wavelet, which has scaling functions, is utilized. Using the cascade algorithm and 2-D separable wavelet transform scheme, an optical wavelet packet filter is constructed based on the selected best bases. Inserting this filter makes the recognition performance better.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
De Cai, Qiaofeng Tan, Yingbai Yan, Guofan Jin, and Qingsheng He "Using optical wavelet packet transform to improve the performance of an optoelectronic iris recognition system", Proc. SPIE 5642, Information Optics and Photonics Technology, (11 January 2005); https://doi.org/10.1117/12.576261
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KEYWORDS
Wavelets

Iris recognition

Image compression

Crystals

Optical filters

Wavelet transforms

Optoelectronics

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