Gender recognition using PCA and DCT of face images
O Smirg, J Mikulka, M Faundez-Zanuy, M Grassi… - … : 11th International Work …, 2011 - Springer
Advances in Computational Intelligence: 11th International Work-Conference on …, 2011•Springer
In this paper we propose a gender recognition algorithm of face images. We have used PCA
and DCT for dimensionality reduction. The algorithm is based on a genetic algorithm to
improve the selection of training set of images for the PCA algorithm. Genetic algorithm
helps to select the images, which best represent each gender, from the image database. We
have evaluated a nearest neighbor classifier as well as a neural network. Experimental
results show a correct identification rate of 85, 9%.
and DCT for dimensionality reduction. The algorithm is based on a genetic algorithm to
improve the selection of training set of images for the PCA algorithm. Genetic algorithm
helps to select the images, which best represent each gender, from the image database. We
have evaluated a nearest neighbor classifier as well as a neural network. Experimental
results show a correct identification rate of 85, 9%.
Abstract
In this paper we propose a gender recognition algorithm of face images. We have used PCA and DCT for dimensionality reduction. The algorithm is based on a genetic algorithm to improve the selection of training set of images for the PCA algorithm. Genetic algorithm helps to select the images, which best represent each gender, from the image database. We have evaluated a nearest neighbor classifier as well as a neural network. Experimental results show a correct identification rate of 85,9%.
Springer
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