Facial Feature Extraction Using Hierarchical MAX(HMAX) Method

Akshaya Pisal, Ravindra Sor, Kishor S. Kinage · 2017

In the digital revolution identifying the attributes of human population has become necessity for social economic benefit distribution, security and surveillance. Age estimation is one of the interesting and challenging research problem from last several years. Estimation of Age is defined as determine particular person age or age group from given face image. Feature extraction is most important focusing area, were pixel level feature, global feature, local feature are extracted from face image. Person's age is determine based on biometric features. In this paper focus is given on feature extraction. We first perform Pre-processing using HSV Color space model and Gaussian filter from given face image then Hierarchical MAX(HMAX) model are used to extract Biologically Inspired features(BIF). This paper compares our feature extraction approach with standard HMAX algorithm for better age estimation. The experimental result shows that our proposed feature extraction method extract more feature and increase response time compared to standard HMAX method.

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