Polychromatic pattern recognition based on color component chaos encoding |
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| Authors: | Xiaopeng Deng Daomu Zhao |
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| Institution: | 1. Department of Physics and Information Engineering, Huaihua University, Huaihua 418008, China;2. Department of Physics, Zhejiang University, Hangzhou 310027, China;1. Department of Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, 32952 Menouf, Egypt;2. Department of Electrical Engineering and Electronics, Liverpool University, L69 3GJ, UK;3. Department of Electrical Engineering, Faculty of Engineering, Alexandria University, Alexandria 21544, Egypt;1. School of Physics and Engineering, Henan University of Science and Technology, Luoyang, Henan 471023, PR China;2. School of Information Science and Engineering, Shandong University, Jinan, Shandong 250100, PR China;1. Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China;2. Department of Photonics Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark;1. Institute of Multi-dimensional Signal Processing, College of Information Engineering, Shenzhen University, Shenzhen, Guangdong, 518000, China;2. Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611-6130, United States of America |
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| Abstract: | In order to overcome the disadvantages which the single-channel system and the multichannel system suffer from some special cases, such as, when there exists a linear relationship between the corresponding color components of the target image and the reference image, a novel method for color pattern recognition is proposed based on color component chaos encoding. In this approach, the color components are first encoded into chaos images and then the encoded images serve as the input images of the single-channel (or multichannel) system. As a result, the color difference resulting from the linear relationship between the corresponding color components of the target image and the reference image can be recognized. Computer simulations prove that this method is valid. |
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