PSO Based Fuzzy-Genetic Optimization Technique for Face Recognition

One of the trending research topics over the world is Face Recognition. There are several methods available to recognize the human faces. Yet new methods are proposed to make the model efficient and accurate. The model is said to be efficient and accurate if the system can recognize the human faces with higher recognition rate with the best time complexity. The algorithms like textural feature descriptors consists of limitations like robustness to noise, the rotation of images, the dimensionality of the dataset which affects the efficiency of the algorithm. We propose a new method to overcome these limitations to give the optimal solution by using optimization techniques. In this paper, the hybrid optimization technique, PSO based fuzzy-genetic optimization technique is proposed to give high level recognition rate better than techniques like local binary patterns, history of gradients and also basic optimization techniques. The recognition rate of the proposed method is 98.84%. This new technique can efficiently find the best fitted features of the image.