Face Recognition using SURF, Median Filter and Particle Swarm Optimization

Volume: 3    Issue: 2

Year of Publication: 2016

Pages: (21-25)

Authors: Anuradha, Mr. Sanjay Yadav

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Abstract

This paper proposes classification-based face detection method using PSO, SURF and Median filter features. Considering the desirable characteristics of spatial locality and orientation selectivity of the PSO, SURF and Median filter, we design filters for extracting facial features from the local image. The feature vector based on PSO, SURF and Median filters is used as the input of the classifier, which is a Feed Forward on a reduced feature subspace learned by an approach simpler than principal component analysis. The effectiveness of the proposed method is demonstrated by the experimental results on testing a large number of images and the comparison with the state-of-the-art method. The image will be convolved with PSO, SURF and Median filters by multiplying the image by PSO, SURF and Median filters in frequency domain. To save time they have been saved in frequency domain before Features is a cell array contains the result of the convolution of the image with each of the forty PSO, SURF and Median filters. For the implementation of this proposed work we use Image Processing Toolbox under the Matlab software.

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Keywords

Face Recognition, SURF Feature, Median and Particle Swarm Optimization (PSO)