This work presents a novel approach to content-based image retrieval in categorical multimedia databases. The images are indexed using a combination of text and content descriptors. The categories are viewed as semantic clusters of images and are used to confine the search space.

This is to certify that I have examined this copy of a master's thesis by Anand Sivaraman and have found that it is complete and satisfactory in all respects, and that any and all revisions required by the final examining committee have been made. ABSTRACT Content-based image retrieval systems retrieve images from a database that are

Texture is widely used in CBIR, and there have been a number of studies over the years to establish which features are perceptually significant. However, it is still diSJicult to retrieve reliably images that the human user would agree are “similar”. This paper reviews a range of computational methods, and compares their performance in class@ing and retrieving imagesporn the Brodatz set. Their ...

We describe the outcome of an effort to understand the behavior of content-based image retrieval (CBIR) technology by examining the behavior of a CBIR system in response to carefully constructed input query images. This work is preliminary and only considers a single CBIR system, SIMPLIcity[4]. We chose this particular system for expediency. It is our intention to develop a methodology suitable...

296-220 Abstract In this paper we present a study of the comparison of the performance of content-based image retrieval systems based on structure [1] with those based on histogram and texture analysis methods, where retrieval is concerned with locating images containing manmade objects. The advantage of using structure in such queries is demonstrated by analyzing an image database containing m...

In this paper we analyze the image retrieval problem in presence of possible foreground disturbances. The foreground may be irrelevant for the retrieval but it occludes the background and hence reduces the retrieval accuracy. We propose the use of a video as a query so that the moving foreground can be extracted. The segmented foreground region is subsequently filled into increase the retrieval...

This paper gives a summary of the content-based Image Retrieval and Content-based Audio Retrieval, which are two parts of the Content-based Retrieval. Content-based Retrieval is the retrieval based on the features of the content. Generally, it is a way to extract features of the media data and find other data with the similar features from the database automatically. Content-based Retrieval can...