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Morphological Primitive Patterns with Grain Components on LDP for Child and Adult Age Classification
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 21 - Number 3 |
| Year of Publication: 2011 |
| Authors: B.Sujatha, Dr.V.Vijaya Kumar, M.Rama Bai |
10.5120/2488-3357
|
B.Sujatha, Dr.V.Vijaya Kumar, M.Rama Bai . Morphological Primitive Patterns with Grain Components on LDP for Child and Adult Age Classification. International Journal of Computer Applications. 21, 3 ( May 2011), 50-55. DOI=10.5120/2488-3357
Abstract
Human beings can easily categorize a person’s age group from an image of the person’s face and are often able to be quite precise in this estimation. This ability has not been pursued in the computer vision community. To address this, the present paper proposes a novel local texture features on facial images that classify adult and child images based on the Morphological primitive patterns with grain components (MPP-g) on a Local Directional Pattern (LDP). A LDP feature is obtained by computing the edge response values in all eight directions at each pixel position and generating a code from the relative strength magnitude. The local descriptor LDP is more consistent in the presence of noise, and illumination changes, since edge response magnitude is more stable than pixel intensity. The proposed MPP-g is rotationally and pose invariant when compared to pattern trends that represents a shape. The experimental result on FGnet database images shows the efficacy of the proposed method.
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