Generating efficient classifiers using facial components for age classification. (2018)

• Record Type: Journal Article
• Authors: Panicker, Sreejit; Selot, Smita; Sharma, Manisha
• Is Part Of: International journal of image mining. Volume 3:Number 1(2018)
• Page Start: 38
• Page End: 47
• Publication Date: 2018
• Subjects: ageing -- age estimation -- texture; Image processing -- Periodicals; Data mining -- Periodicals; 006.42
• Languages: English
• ISSNs: 2055-6039

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.