Face Recognition using DWT Compression and PSO based DCT Feature Selection

摘要：

In this paper, a robust face recognition algorithm based on Discrete WaveJet Transform (DWT), Discrete Cosine Transform (DCT) and Particle Swarm Optimization (PSO) is presented. Initially, 2D-DWT is used to compress the data at various levels, which also removes the high frequency noise from the input image. Then DCT is applied to the resulting image to extract coefficients. Finally, the proposed PSO-based feature selection algorithm is utilized to search the feature space for the optimal feature subset where features are carefully selected according to a well defined discrimination criterion. Experimental results compared to the recently proposed algorithms on the ORL face database show that the proposed approach is promising; it is able to select small subsets and still improve the classification accuracy.

关键词： Face Recognition Discrete Wavelet Transforms Discrete Cosine Transform Feature Selection Particle Swarm Optimization

作者: Yigui SUN Dexiang ZHOU

作者单位: School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China

会议类型: 国际会议

会议名称: Third International Conference on Digital Image Processing(ICDIP 2011)(第三届数字图像处理国际会议)

会议地点: 成都

会议语种:英文

页码: 386-390

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）