700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ ReadersThis Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)
Research Article Open Access
This paper describes a face detection method using Artificial Neural Network (ANN) and Gabor filters. This method achieves rotation invariant and extremely high face detection rate using Gabor wavelets. Gabor filters have optimal localization properties in both spatial and frequency domain. By using these desirable characteristics, Gabor filters extract facial features from the local image. These extracted features work as the input to image classifier which is a Feed Forward Neural Network (FFNN).This network works on a reduced feature subspace learned by an approach simpler than principal component analysis (PCA). Face classification is currently implemented in software. This study gives an impression of Gabor filters in image processing and emphasis on its characteristics of spatial locality and orientation selectivity.
Face detection, Gabor wavelet, feed forward neural network classifier, Multilayer perceptron, Aerospace Engineering,Applied Electronics,Biogenetic Engineering,Biomedical Engineering,Botany,Fluid Dynamics.