Searching for an object in a general image collection using current image retrieval systems, is still a problem. The retrieval results contain many unrelated images. In providing an effective and robust image database, objects in an image need to be extracted. Since the number of stored images can be very large, automation is an important aspect. Image indexing is a technique that extracts obje...

Content-based image retrieval (CBIR) has been an active research topic in the last decade. In this paper we proposed an image retrieval method using global and local features. Firstly, for local features extraction, SURF algorithm produces a set of interest points for each image and a set of 64-dimensional descriptors for each interest points and then to use Bag of Visual Words model, a cluster...

in this paper, the performance of 11 different distances for image retrieval and classification, based on color, shape and texture, is evaluated. the precision-recall measure and the correct classification rate of the k-nn classifier are used to evaluate retrieval and classification performances, respectively. the experimental results for a database of 1000 images from 10 different semantic gro...