Efficient Image Retrieval Using Advanced Clustering SURF

Image retrieval is one of the most exciting and fastest growing research areas in the field of multimedia technology. In this paper, we propose and implement a new image retrieval method that extracts the feature of image using efficient clustering for SURF (Speed Up Robust Feature) scheme, applicable to mobile environments. Since SURF works only on gray-scale images, our clustering SURF is combined with well-known dominant color descriptor to improve the performance of the system. Also, we calculate the feature vector to remove an unnecessary feature, which is located in the sparse region, not to be clustered in final target features. To evaluate the performance of the proposed algorithm, we assess the simulation's performance in terms of average precision on two image databases commonly used. Based on the average precision from all queries, 86% and 79% of all relevant images were retrieved. The result shows that the proposed approach obtains an enough results which are applicable to mobile environments.