WSEAS Transactions on Computers

Print ISSN: 1109-2750
E-ISSN: 2224-2872

Volume 17, 2018

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

Human Facial Age Estimation by Positional Ternary Pattern and Gray-Level Co-Occurrence Matrix

AUTHORS: P. Tamije Selvy, G. Poorani, G. Sathya, P. Seethalakshmi, R. Swathi

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ABSTRACT: -Human facial age estimation is done using image processing. Many applications like forensics, security, and biometrics have attracted much attention in human facial age estimation. Multiclass classification and regression problem are the existing approaches that cast facial age estimation. We propose a positional ternary pattern algorithm that inherits the craniofacial shape with wrinkle and micro texture pattern. And then Gray-Level Co-occurrence Matrix plays a major role in revealing properties of gray levels in texture image. Age estimation based on human face remains a problem in computer vision and pattern recognition. To estimate an accurate age most of the existing system is used and it requires a huge data set attached with age labels. In addition to the proposed approach we proposed the probabilistic neural network that is widely used in classification and pattern recognition problem.

KEYWORDS: - Image processing, Positional Ternary Pattern, gray-Level Co-occurrence Matrix, Probabilistic Neural Network.


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WSEAS Transactions on Computers, ISSN / E-ISSN: 1109-2750 / 2224-2872, Volume 17, 2018, Art. #29, pp. 240-246

Copyright © 2018 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

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