A Meta-Heuristic Optimization Approach for Content Based Image Retrieval using Relevance Feedback Method

With the potential growth of multimedia hardware and applications, the machines have to realize the information by adapting to the internal information. An adaptive content based image retrieval (CBIR) approach based on relevance feedback and Firefly algorithm is proposed in this paper. In addition to the color descriptor, wavelet-based texture descriptor is considered to improve the retrieval performance. 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 demonstrate the feasibility of the approach. Index Terms — Content-based image retrieval, Relevance Feedback, Firefly Algorithm, color descriptor, texture descriptor.