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Title: Generating efficient classifiers using facial components for age classification

Authors: Sreejit Panicker; Smita Selot; Manisha Sharma

Addresses: SSTC, Junwani Bhilai, Chhattisgarh, 491001, India ' SSTC, Junwani Bhilai, Chhattisgarh, 491001, India ' Bhilai Institute of Technology Durg, Chhattisgarh, 491001, India

Abstract: Ageing a natural phenomenon, happens with time and becomes evident as a person grows. An individual undergoes various changes as age progresses. This is noticeable by his or her facial structure and texture which changes as growth accelerate. Facial growing is a standard happening that is sure, and differs from individual to individual subject on the conditions and living susceptibility. Uses of age assertion are seen in areas like Forensic science, security, and furthermore to decide wellbeing of an individual. Facial parameters used for age characterisation can be either structural or textural. In this paper, we have used statistical methodologies for feature extraction. In structural, facial development is considered for characterisation, by figuring the Euclidean separation between the different points of interest on the facial image. The experimental results are significant and remarkable.

Keywords: ageing; age estimation; texture.

DOI: 10.1504/IJIM.2018.093003

International Journal of Image Mining, 2018 Vol.3 No.1, pp.38 - 47

Received: 13 Jan 2017
Accepted: 15 Aug 2017

Published online: 04 Jul 2018 *

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