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Proceedings Paper

Wood surface texture inspection using automatic selection band for wavelet reconstruction
Author(s): Chun-hai Hu; Hai-ping Liang
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Paper Abstract

This paper is focused on the analysis of wood surface inspection to wood machining industries. A defect detection approach for texture image, which uses an efficient image restoration scheme in wavelet domain, is presented. First, the texture image is decomposed by using wavelet base function in terms of the optimum decomposition levels, and then the restoration image can be reconstructed by properly selecting the smooth subimage or the detail subimages at best resolution levels. The homogeneous texture pattern can be effectively removed and only local defects are preserved in the restored image. A subband selection procedure is developed to automatically determine the best reconstruction parameters based on the energy distribution of wavelet coefficients. Then binarized image is received after image segmentation, At last the methods of image post-processing mathematical morphology were used in segmentation image. Experiments demonstrate the validity of the method, and show the potential possibility of real-time processing in an on-line wood surface inspection.

Paper Details

Date Published: 31 December 2008
PDF: 7 pages
Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 713038 (31 December 2008); doi: 10.1117/12.819675
Show Author Affiliations
Chun-hai Hu, Yanshan Univ. (China)
Hai-ping Liang, Yanshan Univ. (China)

Published in SPIE Proceedings Vol. 7130:
Fourth International Symposium on Precision Mechanical Measurements
Yetai Fei; Kuang-Chao Fan; Rongsheng Lu, Editor(s)

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