تشخیص چهره با استفاده از شبکه عصبی و تبدیل موجک گابور

This paper is based on classifications of the features of a face detected using Gabor filter feature extraction techniques in image processing. The feature vector based on Gabor filters used as the input of the classifier, which is a Feed Forward Neural Network (FFNN) on a reduced feature subspace learned by an approach simpler than Principal Component Analysis (PCA). The effectiveness of the proposed method is demonstrated by the experimental results on testing large number of images and comparisons with state of the art method. Face detection and recognition has many applications in a variety of fields such as security systems, video conferencing and identification.