Stochastic firefly for image optimization

With the rapid growth of technology the machines has to realize the information by adapting to the internal information. Due to potential growth of multimedia hardware and applications, the information retrieval has been analyzed by content based image retrieval (CBIR). Feature extraction has been done with the Euclidean distance estimation between the pixels; relevance feedback (RF) based approach but all concerns with the extraction of image accuracy. This research work has a focused approach to increase the performance by optimizing image feature by adopting with the firefly algorithm (FA). The experimental results compared with the other optimization algorithms like particle swarm optimization and genetic algorithm to identify the difference with respect to the model in terms of precision and recall.