A facial expression recognition algorithm based on local binary pattern and empirical mode decomposition

被引：0

作者：

Yang, Hong ^{[1
,3
]}

Zhu, Deli ^{[2
]}

机构：

[1] Institute of Information Science and Technology, Northwestern University, Xian

[2] School of Computer and Information Science, Chongqing Normal University, Chongqing

[3] Teaching Affairs Office, Chongqing Normal University, Chongqing

来源：

Open Electrical and Electronic Engineering Journal | 2014年 / 8卷 / 01期

关键词：

EMD; Facial expression recognition; LBP;

D O I：

10.2174/1874129001408010599

中图分类号：

学科分类号：

摘要：

To improve the efficiency of facial expression recognition, this paper puts forward a kind of recognition algorithm based on local binary pattern (LBP) and empirical mode decomposition (EMD). First of all, process the empirical mode decomposition into the preprocessing facial image, and bring forward many a high frequency images instead of the original image; then, divide the sub domain of the high frequency image and obtain the sub domain LBP histogram and full face histogram; finally, identify the expression of the generated LBP histogram. Through the experiment on JAFFE database, it shows that the method is effective for facial expression recognition. © Yang and Zhu; Licensee Bentham Open.

引用

页码：599 / 604

页数：5

共 9 条

[1]

Ojala T., Pietikainen M., Harwood D., A comparative-study of texture measures with classification based on feature distributions, Pattern Recognition, pp. 51-59, (1996)

[2]

Liu L., Xie Y.X., Wei Y.M., Lao S.Y., Survey of Local Binary Pattern method, Journal of Image and Graphics, 19, 12, pp. 1696-1720, (2014)

[3]

Hadid A., Ahonen T., Pietikinen M., Handbook of Texture Analysis, pp. 347-373, (2008)

[4]

Hadid A., The local binary pattern approach and its applications to face analysis, Proceedings of International Workshops on Image Processing, Theory, Tools and Application, pp. 1-9, (2008)

[5]

Zhao G.Y., Pietika M., Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions, IEEE Transactions on pattern analysis and machine intelligence, 29, 6, (2007)

[6]

Shan C.F., Gong S.G., Peter W.M., Robust facial expression recognition using local binary patterns, IEEE International Conference on Image Processing, 2, pp. 370-373, (2005)

[7]

Smith R.S., Windeatt T., Facial Expression Detection using Filtered Local Binary Pattern Features with ECOC Classiers and Platt Scaling, JMLR: Workshop and Conference Proceedings, 11, pp. 111-118, (2010)

[8]

Lajevardi S.M., Hussain Z.M., Facial expression recognition using log-gabor filters and local binary pattern operators, (2009)

[9]

Luo Y., Wu C.M., Zhang Y., Facial expression recognition based on fusion feature of PCA and LBP with SVM, Optik, 124, pp. 2767-2770, (2013)

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