FPGA and Optimization Technique Based Human Gender Classification
Journal Title: International journal of Emerging Trends in Science and Technology - Year 2017, Vol 4, Issue 10
Abstract
Gender identification from face features plays an important role in security, surveillance systems. The research is carried out with different methods in feature detection , feature extraction, and different classification algorithms. And also different processing platforms are used. In this paper the identification of gender from face has been proposed using MATLAB simulation platform and FPGA as processing platform. Firstly, the image to be examined is taken from pre-recorded video. Then the control points are detected in MATLAB and the data is transferred to FPGA platform for feature extraction. To make the system optimized, here optimization algorithm that is Ant Colony Optimization (ACO) is used. With the help of ACO, optimized features are extracted from the detected control points. Again the extracted data is send to MATLAB. Finally, with the help of Artificial Neural Network, the extracted data is tested and gender is identified
Authors and Affiliations
Sharvari A. Kulkarni
Keywords
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