A Robust Method for Face Detection based on Wavelet Transform and optimized feature selection using Ant Colony Optimization in Support Vector Machine

  Mahesh Tawade,  Sudesh Gupta

Face recognition method suffered from problem of feature selection process. The feature selection process in pattern recognition and recognition play an important role. The current method of face recognition system only focus on local, global and neural network process of feature extraction and process for recognition. The optimized feature selection process improves the recognition ratio of face recognition. In this dissertation we proposed a new method for face recognition based on wavelet transform function for feature extraction and for selection of feature of facial image used ant colony optimization technique for selection of feature for classification of support vector machine. The optimized feature selection process pass the data of most similar for classifier for classified data for recognition process. The optimized process of data reduces the unclassified region of support vector machine and improves the performance of face recognition..In this dissertation we modified the matching technique for face recognition using multi-class SVM and ant colony optimization. For the modification of pattern classification binary support vector classifier used

Keywords- SVM, Face Detection, feature extraction

Unique Identification Number - IJEDR1604003
Page Number(s) - 17-19
Pubished in - Volume 4 | Issue 4 | October 2016
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Mahesh Tawade,  Sudesh Gupta,   "A Robust Method for Face Detection based on Wavelet Transform and optimized feature selection using Ant Colony Optimization in Support Vector Machine", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.4, Issue 4, pp.17-19, October 2016, Available at :http://www.ijedr.org/papers/IJEDR1604003.pdf