JIP_V2_N4_RP1 Gandu Bharat Burusu Rajesh Kumar Journal on Image Processing 2349-6827 2 4 1 9 Structural Patterns, Facial Image, Age Group Estimation, Diagonal Pattern, Central Pattern The present paper derives a new approach for estimating the age group of a person based on structural patterns of an edge image identified in a human face image. This approach uses canny edge operator algorithm for extracting the edges of the image because canny edge operator gives more edges. In this approach, edges are most important because, wrinkles are formed on face when age is growing. When wrinkles are formed on facial image, automatically more edge information is available. This approach uses a structural concept. The present study derived four distinct structural patterns on each 3x3 sub window of facial edge image i.e. Right Diagonal Pattern (RDP), Left Diagonal Pattern (LDP), Vertical Central Line Pattern (VCLP) and Horizontal Central Line Pattern (HCLP) pattern. The central pixel value of the 3x3 sub image is considerable in all four patterns. Based on formation of those four structural patterns, i.e. frequency of occurrences of structural patterns estimate the human age group into five age groups i.e. Child (0 to 9 years), Young (10 to 20 years), Young Adult (21-35), Adult (36 to 50 years) and Senior Age (>50 years). The efficiency of the proposed method is calculated by applying it on different huge facial databases like FgNET and Morph. The proposed method shows high rate of classification when compared with the other existing methods. October - December 2015 Copyright © 2015 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=3685