Image retrieval has great potential for a variety of tasks in medicine but is currently underdeveloped. For the ImageCLEF 2005 medical task, we developed a context-based retrieval system. We then conducted our experiment using an automatic query, a manual query, and a manual/visual query. The best results were obtained from manual modification of queries, while combining those results with data...

This paper presents a multi-mode indexing scheme for effective content-based image retrieval. Three types of indices are identified: visual indices for quantifiable visual information, semantic indices for non-quantifiable semantic information, keywords indices for keywords or free text. The underlying index structures are the HG-tree and the signature file. The HG-tree is one of the most promi...

Algorithms of Content-Based Image Retrieval (CBIR) have been well developed along with the explosion of information. These algorithms are mainly distinguished based on feature used to describe the image content. In this paper, the algorithms that are based on color feature and texture feature for image retrieval will be presented. Color Coherence Vector based image retrieval algorithm is also a...

Trademark Image Retrieval is playing a vital role as a part of CBIR System. Trademark is of great significance because it carries the status value of any company. To retrieve such a fake or copied trademark we design a retrieval system which is based on hybrid techniques. It contains a mixture of two different feature vector which combined together to give a suitable retrieval system. In the pr...

A content-based image retrieval mechanism to support complex similarity queries is presented. The image content is defined by three kinds of features: quantifiable features describing the visual information, non-quantifiable features describing the semantic information, and keywords describing more abstract semantic information. In correspondence with these feature sets, we construct three type...

Content-based image retrieval, which provides convenient ways to retrieve images from large image databases, has been studied actively. However, many previous image retrieval techniques do not look at regions in an image. In this paper, we present a novel region matching method for contentbased image retrieval. In this method, the region dependences in each image are first computed in order to ...

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The current most desirable image retrieval feature is retrieving images based on their semantic content. Currently there are two major image retrieval paradigms that attempt to provide this: text-based metadata image retrieval and content-based image retrieval. In practical applications, both have limitations. In this paper, we discuss an ontology-based image retrieval approach that aims to sta...

Sensing and processing multimedia information is one of the basic traits of human beings: The audiovisual system registers and transports surrounding images and sounds. This complex re-cording system, complemented by the senses of touch, taste, and smell, enables perception and provides humans with data for analysing and interpreting the environment. Imitating this perception and the simulation...