Interactive image retrieval using M-band wavelet, earth mover’s distance and fuzzy relevance feedback

We propose an interactive content based image retrieval (CBIR) system using M-band wavelet features with earth mover’s distance (EMD). A fuzzy relevance feedback (FRF) method is proposed to enhance the retrieval mechanism in order to retrieve more images which are semantically close to the query. M × M sub-bands coefficient are used as primitive features, on which, for each pixel, energies are computed over a neighborhood and are taken as features for each pixel to characterize its color and texture properties. Based on the energy property, pixels are clustered using fuzzy C-means algorithm to obtain an image signature. The EMD is used as a distance measure between the signatures for different images of the database. Combining information both from relevant and irrelevant images marked by the user, fuzzy entropy based feature evaluation mechanism is used for automatic computation of revised feature importance and similarity distance at the end of each iteration. The proposed CBIR system performance using M-band wavelets feature are compared to that of Moving Picture Expert Group-7 visual features which have almost become a standard benchmark for both video and image representation and comparison. The proposed FRF technique using EMD is compared with different other similarity measures to test the effectiveness of the system on standard image database.