Paper
8 July 2011 Face recognition using DWT compression and PSO-based DCT feature selection
Yigui Sun, Dexiang Zhou
Author Affiliations +
Proceedings Volume 8009, Third International Conference on Digital Image Processing (ICDIP 2011); 800921 (2011) https://doi.org/10.1117/12.896095
Event: 3rd International Conference on Digital Image Processing, 2011, Chengdu, China
Abstract
In this paper, a robust face recognition algorithm based on Discrete Wavelet 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.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yigui Sun and Dexiang Zhou "Face recognition using DWT compression and PSO-based DCT feature selection", Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 800921 (8 July 2011); https://doi.org/10.1117/12.896095
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Cited by 4 scholarly publications.
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KEYWORDS
Particle swarm optimization

Facial recognition systems

Discrete wavelet transforms

Detection and tracking algorithms

Feature selection

Particles

Feature extraction

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