Face and gender Recognition Using Genetic Algorithm and Hopfield Neural Network

This paper describes a face recognition system for personal identification and verification using genetic algorithm and Hopfield Neural Network. This FRS system is also being trained for gender identification. Face recognition system consists of three steps. At the initial stage of this system some pre-processing are applied on the input image. Secondly, face features are extracted, which will be taken as the input of the eight parallel Hopfield neural network and genetic algorithm (GA). In the third step, classification is carried out by using Hopfield neural network and GA to identify gender. The proposed approaches can be tested on a number of face images. Sex-recognition in faces is a prototypical pattern recognition task and it appears to follow no simple algorithm. It is modifiable according to fashion (makeup, hair etc).While ambiguous cases exist, for which we must appeal to other cues such as physical build (if visible), voice pattern (if audible) and mannerisms.

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