Image retrieval from image databases is usually performed by using global image characteristics such as texture or colour. The use of local image information is highly desirable when only part of the image is of interest, but global approaches are not well suited to this. An original solution was introduced in [11] using invariant local signal characteristics. This paper extends this contribution by extending the set of invariants considered to allow illumination change. Then it is shown that the invariant distribution is far from uniform and a probabilistic indexing scheme is proposed. Experimental results validate the approch and the different method are discussed. The main result is that it is much more valuable to increase the discrimant power of the vector used to perform the indexing process; The Bayesian decision improves the standard method, but this improvement is much more limited than expected.

We describe an algorithm for computing an image signature, suitable for first-stage screening for duplicate images. Our signature relies on relative brightness of image regions, and is generally applicable to photographs, text documents, and line art. We give experimental results on the sensitivity and robustness of signatures for actual image collections, and also results on the robustness of signatures under transformations such as resizing, rescanning, and compression. 1.

Content-based image retrieval system retrieves an image from a database using visual information. Among approaches to expressing visual aspects in queries, "query by sketch" is most convenient and expressive. However, the query drawn by the user is typically quite different from the target image. In this paper, a matching algorithm for imperfect queries is presented. The algorithm measures the similarity between the query and each image stored in the database based on their topological structures that are represented by prime edge graphs. Experimental results show that the system retrieves the intended image with a high similarity score even from a partial or shifted query. Keywords: content-based image retrieval, image database, query by sketch, matching, similarity 1

Abstract-The content based image retrieval(CBIR) is one of the most popular, rising research areas of the digital image processing. Content-based image retrieval information systems use information extracted from the content of query. In these tools, images are manually annotated with keywords and then retrieved using text- based search methods. The goal of CBIR is to extract visual content of an image automatically, like color, texture, or shape. This paper aims to introduce the problems and challenges concerned with the design and the creation of CBIR systems, which is based on a free hand sketch (Sketch based image retrieval – SBIR). With the help of the existing methods, revealed that the proposed algorithm is better than the existing algorithms, which can handle the informational gap between a sketch and a colored image. Overall, the results show that the sketch based system allows users an intuitive access to searchtools. Experimental results show that the system retrieves the intended image with a high similarity score even from a partial or shifted query. Index Terms- k-medoids clustering algorithm, image similarity matching algorithm. I.