Detection, Segmentation and Recognition of Face and its Features Using Neural Network

Face detection and recognition has been prevalent with research scholars and diverse approaches have been incorporated till date to serve purpose. The rampant advent of biometric analysis systems, which may be full body scanners, or iris detection and recognition systems and the finger print recognition systems, and surveillance systems deployed for safety and security purposes have contributed to inclination towards same. Advances has been made with frontal view, lateral view of the face or using facial expressions such as anger, happiness and gloominess, still images and video image to be used for detection and recognition. This led to newer methods for face detection and recognition to be introduced in achieving accurate results and economically feasible and extremely secure. Techniques such as Principal Component analysis (PCA), Independent component analysis (ICA), Linear Discriminant Analysis (LDA), have been the predominant ones to be used. But with improvements needed in the previous approaches Neural Networks based recognition was like boon to the industry. It not only enhanced the recognition but also the efficiency of the process. Choosing Backpropagation as the learning method was clearly out of its efficiency to recognize nonlinear faces with an acceptance ratio of more than 90% and execution time of only few seconds.

Detection of Face using Viola Jones and Recognition using Back Propagation Neural Network

Detection and recognition of the facial images of people is an intricate problem which has garnered much attention during recent years due to its ever increasing applications in numerous fields. It continues to pose a challenge in finding a robust solution to it. Its scope extends to catering the security, commercial and law enforcement applications. Research for moreover a decade on this subject has brought about remarkable development with the modus operandi like human computer interaction, biometric analysis and content based coding of images, videos and surveillance. A trivial task for brain but cumbersome to be imitated artificially. The commonalities in faces does pose a problem on various grounds but features such as skin color, gender differentiate a person from the other. In this paper the facial detection has been carried out using Viola-Jones algorithm and recognition of face has been done using Back Propagation Neural Network (BPNN).