Result Oriented Based Face Recognition using Neural Network with Erosion and Dilation Technique

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 seminar, 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
DOI: 10.17762/ijritcc2321-8169.160419