Age Grouping with Central Local Binary Pattern based Structure Co-occurrence Features

In this paper, we introduced new Age Classification method with Contrast, Correlation, Energy, and Local homogeneity features on Central Local Binary Pattern based Structure. Local Binary Pattern is computed on the image and then Central Local Binary Pattern based Structure is formed, and on this matrix Cooccurrence features Contrast, correlation, energy and homogeneity are evaluated in four directions 0°, 45°, 90° and 135. The proposed Age Classification algorithm is trained and tested with FG-Net aging database and scanned facial images has shown considerable improvement in the grouping of adult and child groups.