Abstrakt

MORPHOLOGICAL METHOD, PCA AND LDA WITH NEURAL NETWORKSFACE RECOGNITION

Sushma Jaiswal, Dr. Sarita Singh Bhadauria, Dr. Rakesh Singh Jadon

The problem is, these forms of machine identification and verification aren’t very secure, because they can be given away, taken away, or lost and motivated people have found ways to forge or circumvent these credentials. The ultimate form of electronic verification of a person’s identity is biometrics; using a physical attribute of the person to make a positive identification. So we need a system, which is similar to the human eye in some sense to identify a person. To cater this need and using the observations of human psychophysics, face recognition as a field emerged. Different approaches have been tried by several groups, working world wide, to solve this problem. Many commercial products have also found their way into the market using one or the other technique. But so far no system or technique exists which has shown satisfactory results in all circumstances. A comparison of these techniques needs to be done. In this paper, we will try to do a comparative study of the performances of three algorithms - PCA, LDA and Morphological methods for face recognition.