Symmetrical Analysis of Different Shape Matching and Object Recognition for 2D and 3D Faces

Abstract

Object recognition, Shape matching and pattern recognition plays an important role in the field of newlinecomputer vision. Now a day s many techniques are available for recognizing object efficiently and newlineaccurately. Still a lot of researches are going on, for enhancing the recognition techniques for real newlinetime and dynamic object with different challenges. Identification of object will lead to convex the newlineshape in different environment and it requires more precise techniques so that the convergence newlinefactor is high and error is low for improved recognition rate. Shape is crucial and important aspect newlinefor image visualization. Shape of an object is a group of pixels which is used to call an image. In newlineday to day activities a number of biometric techniques are available for recognizing humans like eye newlineor iris recognition, finger print recognition, gait recognition, face recognition. Face is an important newlinepart of human being and requires detection for different applications like security, forensic newlineinvestigation. newlineResearcher had studied about various methodologies used for 2D and 3D face recognition and face newlineidentification, its advantage and disadvantages. Earlier many researches tried to eliminate the face newlinerecognition challenges, improve accuracy and recognition rate on different face database like ORL, newlineYALE, AR, FERET, LFW and so on.