A Method of Image Texture Feature Analysis Base on Wavelet Decomposition and its Application

Ya Biao Li; Bao Guang Wang; Wen Wen Li

doi:10.4028/www.scientific.net/AMM.130-134.381

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 130-134A Method of Image Texture Feature Analysis Base on...

A Method of Image Texture Feature Analysis Base on Wavelet Decomposition and its Application

Abstract:

A method for analyzing the textural features of image is put forward by using the wavelet decomposition. That is used to measure color difference of ceramic tiles on-line. A linear array color CCD camera is used to grab the image of ceramic tiles, and then the image is pretreated. Two level wavelet decomposition is used on the ceramic tile image, and the energy feature of each sub-graph is extracted. The energy feature will be used as a feature matrix,and it can be carried out the classfication according to minimum distance classifier. It can reflect spatial relationship of color more effectively, when contrast with the color histogram, which is used as a traditional method. Experiments show that it is effective using wavelet analysis on image processing,and the sort results are approximately in accordance with the artificial detection.

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Periodical:

Applied Mechanics and Materials (Volumes 130-134)

Pages:

381-384

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.130-134.381

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Online since:

October 2011

Authors:

Ya Biao Li, Bao Guang Wang, Wen Wen Li

Keywords:

CCD, Color-Difference, Online Measuring, Two Dimension Wavelet Decomposition

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References

[1] NEWMAN T S, JAIN A K. A survey of automated visual inspection [J]. Computer Vision and Image Understanding, 1995, 61(2): 231-262.

DOI: 10.1006/cviu.1995.1017

Google Scholar

[2] MALALAS E N, PETRAKIS E G M, ZERVAKIS M, et al. A survey on industrial vision systems, Applications and Tools [J]. Image and Vision Computing, 2002, 21(2): 171-188.

DOI: 10.1016/s0262-8856(02)00152-x

Google Scholar

[3] LI Wei Qing. Techniques of chromatism classification based on artificial intelligence [J]. Computer Engineering and Design, 2007. 28（13）: 3141-3144.

Google Scholar

[4] LIU Jun-mei. Technology of texture feature extraction based on wavelet [J]. Microcomputer & Its Applications, 2007. 6: 106-112.

Google Scholar

[5] Wang Gaimei. Texture Image Retrieval Based-on Wavelet Package Transformation [J ] Computer Engineering and Applications2004(18) 43-44.

Google Scholar