Surface Defect Inspection of Cold Rolled Strips with Features Based on Adaptive Wavelet Packets
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概要
- 論文の詳細を見る
The defects in the cold rolled strips have textural characteristics, which are nonuniform due to its irregularities and deformities in geometrical appearance. In order to handle the textural characteristics of images with defects, this paper proposes a surface inspection method based on textural feature extraction using the wavelet transform. The wavelet transform is employed to extract local features from textural images with defects both in the frequency and in the spatial domain. To extract features effectively, an adaptive wavelet packet scheme is developed, in which the optimum number of features are produced automatically through subband coding gain. The energies for all subbands of the optimal quadtree of the adaptive wavelet packet algorithm and four entropy features in the level one LL subband, which correspond to the local features in the spatial domain, are extracted. A neural network is used to classify the defects of these features. Experiments with real image data show good training and generalization performances of the proposed method.
- 社団法人電子情報通信学会の論文
- 1997-05-25
著者
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CHOI Chong-Ho
School of Electrical Engineering and Computer Science, Seoul National University
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Choi Chong-ho
School Of Electrical Engineering And Computer Science Seoul National University
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Choi Chong-ho
School Of Electrical Engineering Seoul National University
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LEE Chang
School of Computer Science and Engineering, Chung-Ang University
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CHOI Jun
School of Electrical Engineering, Seoul National University
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CHOI Se
Technical Research Laboratories, Pohang Iron and Steel Co., Ltd.
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Choi Se
Technical Research Laboratories Pohang Iron And Steel Co. Ltd.
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Lee Chang
School Of Computer Science And Engineering Chung-ang University
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Choi J
Korea Advanced Inst. Sci. And Technol. Taejon Kor
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Lee Chang
School Of Electrical Engineering Seoul National University
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Choi Chong-ho
School Of Electrical Engineering And Computer Science Asri Seoul National University
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Choi Jun
School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, Gyeonggi 440-746, Korea
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