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Genetic Algorithm Optimized ANN Technique for Gait Recognition

	International Journal of Scientific Research and Engineering Development (IJSRED)	Full Text:
	Published Issue : Volume-4 Issue-2
	Year of Publication : 2021
	Unique Identification Number : IJSRED-V4I2P80
	Authors : Saima Farooq, Simranjit Kaur, Satnam Singh Dub
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Abstract :

Gait recognition aims essentially to address this problem by recognizing people based on the way they walk. The study of human gait has been increased extensive interests in various fields such as clinical analysis, computer animation, athletic performance analysis, visual surveillance, robotics and biometrics. Gait Biometrics is a new powerful tool for reliable human identification and it makes use of human physiology characteristics such as face, iris, finger prints and hand geometry for identification. The Genetic Algorithm based optimization combines computer vision, pattern recognition, statistical inference, and optics. This work employs a gait recognition process with optimization of binary silhouette-based input images using Genetic Algorithm (GA) and Artificial Neural Network (ANN) based recognition i.e. a GA-NN gait feature optimization system. The performance of the recognition method depends significantly on the quality of the extracted and GA-optimized binary silhouettes. The system is implemented in MATLAB.