Neural Network Based Face Recognition Using Erosion and Dilation Technique: A Review

Abstract

It has been observed that many face recognition algorithms fail to recognize faces after plastic surgery and wearing the spec/glasses which are the new challenge to automatic face recognition.  Face detection is one of the challenging problems in the image processing. This project, introduce a face detection and recognition system to detect (finds) faces from database of known people.

To  detect  the  face  before  trying  to recognize it saves a  lot of work, as only a restricted region  of  the  image  is  analyzed, opposite to many  algorithms  which  work considering the whole image. In This , we gives  study on Face Recognition After Plastic Surgery  (FRAPS) and  after wearing the spec/glasses  with careful analysis  of the effects on face appearance and its challenges to face recognition.

 To address FRAPS and wearing the spec/glasses  problem, an ensemble of An Optimize Wait Selection By Genetic Algorithm For Training Artificial Neural Network Based On Image Erosion  and Dilution Technology. Furthermore, with our impressive results, we suggest that face detection should be paid more attend to. To address this problem, we also used Edge detection method to detect i/p image properly or effectively. With this Edge Detection also used genetic algorithm to optimize weight using artificial neural network (ANN)and save that ANN file to database .And use that  ANN file to compare face recognition in future .