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Authors
Affiliations
1 Department of Computer Science and Engineering, Sri Aditya Engineering College, IN
2 Department of Computer Science and Engineering, Rajeev Gandhi Memorial College of Engineering and Technology, IN
3 Department of Computer Science and Engineering, Anurag Group of Institutions, IN
Source
ICTACT Journal on Image and Video Processing, Vol 5, No 2 (2014), Pagination: 926-931
Abstract
The present paper extended the work carried out by Kumar et. al. [10] on Third order Neighbourhood LBP (TN-LBP) and derived an approach that estimates pattern trends on the outer cell of TN-LBP. The present paper observed and noted that the TN-LBP forms two types of V-patterns on the outer cell of TN-LBP i.e. Outer Right V Patterns (ORVP) and Outer Left V Patterns (OLVP). The ORLP and OLVP of TN-LBP consist of 5 pixels each. The present paper derived Grey Level Co-occurrence Matrix (GLCM) features based on LBP values of ORVP and OLVP. This GLCM is named as ORLVP-GLCM (Outer cell Right and Left V-Patterns of GLCM) and on this four features are evaluated to classify human into child (0 to 12 years), young (13 to 30 years), middle aged (31 to 50 years) and senior adult (above 60 years). The proposed method is experimented on FGNET, GOOGLE and Scanned facial images and the results are compared with the existing methods. The results demonstrate the efficiency of the proposed method over the existing methods.
Keywords
GLCM, LBP-Code, Outer Layer, Size of GLCM.
