DISCERNING FACIAL AGE FROM DIGITAL IMAGE THROUGH COMPONENTIAL TEXTURE MANIFOLD ALGORITHM

Face renders the hints which delineate the details of the person. The major expressions and features are used in plethora of applications such as decision making, digital accessing, applications, secured logins, passport renewal, investigation with regard of missing person, finding details of a person with image and so on. Face detection, age estimation, facial actions, gesture recognition are all bestowed in digital applications. In spite of various researches continued there is an urge to evolve a well sophisticated system to automate this process with least flaw. This research is focused on the system which can discern the age with aid of the input image of the person with better accuracy with the inclusion of images of both male and female belonging to various age groups. Componential texture manifold algorithm is used to identify the facial age value of the person from the received face image. The enhancement is obtained with versatile database encompassing images of various age groups, intra and inters age group images, twin images, celebrity images, images with and devoid makeup effects. Own database FG-NET and CACD were used. The testing was done on 1000images and the results have shown 89.5% accuracy.