A Method for Face Detection based on Wavelet Transform and optimised feature selection using Ant Colony Optimisation in Support Vector Machine
|Sanjay Kumar Pal, Uday Chourasia and Manish Ahirwar
Department of CSE, University Institute of Technology, RGPV, Bhopal, India
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Face detection method suffered from problem of feature selection process. The feature selection process in pattern recognition and detection play an important role. The current method of face detection system only focus on local, global and neural network process of feature extraction and process for detection. The optimised feature selection process improves the detection ratio of face detection. In this paper we proposed a new method for face detection based on wavelet transform function for feature extraction and for selection of feature of facial image used ant colony optimisation technique for selection of feature for classification of support vector machine. The optimised feature selection process pass the data of most similar for classifier for classified data for detection process. The optimised process of data reduces the unclassified region of support vector machine and improves the performance of face detection. Our proposed method compare with PCA and SVM method for detection of group image. Our empirical result shows that better performance in compression of PCA and Support Vector machine.