Research on the Application of Pattern Recognition in the Intelligent Identification of Wallpaper Labeling

Abstract:

In order to realize the intelligent identification of wallpaper labeling, the wallpaper texture and the characteristic of color are comprehensively considered in this paper to rich the pattern feature space. Firstly, the suitable GLCM (gray level-gradient co-occurrence matrix)is constructed to describe the texture feature and extract the feature parameters; And the parameters of color low order matrix are picked up in the RGB color space to constitute mode characteristic vector together. Secondly, to reduce the computation and improve the describing abilities, the Simulated Annealing Algorithm is applied to select feature value from 17 feature parameters. Lastly, the integrated classifier of BP neural network is designed to achieve 94.03% overall recognition rate, which is higher than the traditional one. The experiment results also have shown that this method is effective.

• Periodical: Applied Mechanics and Materials (Volume 65)
• Pages: 518-523
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.65.518
• Online since: June 2011
• Authors: Ye Qin Wang, Yu Qing Wang, Liang Hai Chen
• Keywords: Color Lower Order Matrix, GLCM, Integrated BP Neural Network, Pattern Recognition, Wallpaper

References

[1] Shizhong Gao. Analysis of fabric texture based on GLCM, Computer Engineering and Design, Papers29 (16), 4385-4388 (2008).

[2] Haiying Zhao, Yueping Feng, Shuqiang Wei, Zhengguang Xu. Texture feature extraction of Xinjiang folk art patterns based on varying parameters of GLCM, Journal of Jilin University(Engineering and Technology Edition), Papers40 (5), 1345-1349 (2010).

[3] Xuebing Bai , KeQi Wang, Hui Wang . Research on the classification of wood texture based on Gray Level Co-occurrence Matrix,. Journal of Harbin Institute of Technology, Papers 37 (12), 1667-1670 (2005).

[4] Haralick, R.M. Statistical and structural approaches to texture[C]. Proceedings of the IEEE, 1979: 786-804.

[5] Christoph Palm. Color and Texture classification by integrative Co-occurrence matrices[J]. Pattern Recognition, 2004, 37(5): 965-976.

DOI: 10.1016/j.patcog.2003.09.010

[6] M. Stricker and M. Orengo, Similarity of Color Images, Proc. IS&T/SPIE. Conf. on Storage and Retrieval for Image and Video Databases, San Jose, CA, (1993).

DOI: 10.1117/12.205308

[7] Zhenhua Ma, [ Math Handbook of Modern Application], Beijing: Tsinghua University Press, 48-53 158-159(2003).

[8] Fang Liu, Gaimei Wang. Image Retrieval Based on Combined Color Features,. Computer Engineering and Applications, Papers (16), 83-85 (2003).

[9] Jixiang Sun, [Modern Pattern Recognition], Beijing: Higher Education Press, 252-254(2008).

[10] Hui Wang, Research on the pattern recognition methods of wood surface texture based on GLCM", Harbin, Northeast Forestry University, a master, s thesis, (2007).