Journal of the Korean Society of Industry Convergence (한국산업융합학회 논문집)
- Volume 6 Issue 1
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- Pages.23-29
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- 2003
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- 1226-833X(pISSN)
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- 2765-5415(eISSN)
Image Feature Extraction Using Independent Component Analysis of Hybrid Fixed Point Algorithm
조합형 Fixed Point 알고리즘의 독립성분분석을 이용한 영상의 특징추출
- Cho, Yong-Hyun (School of Compter & Information Comm., CUD.) ;
- Kang, Hyun-Koo (Dept. of Eletronics, YCST.)
- Received : 2002.10.17
- Accepted : 2003.01.20
- Published : 2003.02.28
Abstract
This paper proposes an efficient feature extraction of the images by using independent component analysis(ICA) based on neural networks of the hybrid learning algorithm. The proposed learning algorithm is the fixed point(FP) algorithm based on Newton method and moment. The Newton method, which uses to the tangent line for estimating the root of function, is applied for fast updating the inverse mixing matrix. The moment is also applied for getting the better speed-up by restraining an oscillation due to compute the tangent line. The proposed algorithm has been applied to the 10,000 image patches of
Keywords
- independent component analysis;
- fixed point algorithm;
- moment;
- Garbor function;
- wavelet function;
- feature extraction