An improved grid search algorithm and its application in PCA and SVM based face recognition

被引：0

作者：

Yao, Yukai ^{[1
]}

Zhang, Long ^{[1
]}

Liu, Yang ^{[1
]}

Ma, Min ^{[1
]}

Ji, Dongsheng ^{[1
]}

Yang, Qingjun ^{[1
]}

Chen, Xiaoyun ^{[1
]}

机构：

[1] School of Information Science and Engineering, Lanzhou University

来源：

Journal of Computational Information Systems | 2014年 / 10卷 / 03期

关键词：

Face recognition; Grid search; Image preprocessing; PCA; SVM;

D O I：

10.12733/jcis9624

中图分类号：

学科分类号：

摘要：

In this article, we propose an effective grid search method and apply it in the PCA and SVM based face recognition. Firstly, image preprocessing is employed to reduce the information of face images meanwhile enhance their distinctive features; Secondly, we extract features with PCA algorithm and then deliver the dimension reduced data to SVM for classification. During the process of building SVM classifier, our improved multi-parameter grid search algorithm is adopted to advance the accuracy and spatiotemporal efficiency of its parameter optimization. Experiments show the high efficiency and better recognition rate of our method. © 2014 Binary Information Press.

引用

页码：1219 / 1229

页数：10

共 16 条

[1] Li S.Z., Handbook of Face Recognition, (2011)
[2] Wang P., Zhou K., Zhou F., Et al., Optical textures classification of coke microscopic image based on SVM, Computer Application and System Modeling (ICCASM), 2010 International Conference on, 4, (2010)
[3] Bagade S.S., Shandilya V.K., Use of histogram equalization in image processing for image enhancement, International Journal of Software Engineering Research and Practices, 1, 2, pp. 6-10, (2011)
[4] Jean R., Demosaicing with the bayer pattern, Red, 33, R53, (2010)
[5] Zhou J., Ji Z., Shen L., Et al., Pso based memetic algorithm for face recognition gabor filters selection, Memetic Computing (MC), 2011 IEEE Workshop on, pp. 1-6, (2011)
[6] Yang J., Zhang D., Frangi A.F., Et al., Two-dimensional PCA: A new approach to appearancebased face representation and recognition, Pattern Analysis and Machine Intelligence, IEEE Transactions on, 26, 1, pp. 131-137, (2004)
[7] Gottumukkal R., Asari V.K., An improved face recognition technique based on modular PCA approach, Pattern Recognition Letters, 25, 4, pp. 429-436, (2004)
[8] Phillips P.J., Support vector machines applied to face recognition, (1998)
[9] Song X., Jiang X., Luo J., Et al., SVM parameter selection based on the bound of structure risk, Tech Review, 29, (2011)
[10] Wang X., Zhong Y., Statistical learning theory and state of the art in SVM, Cognitive Informatics, 2003.Proceedings. The Second IEEE International Conference on, pp. 55-59, (2003)

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