The use of visual features in text-based ad-hoc image retrieval is challenging. Visual and textual information have so far been treated equally in terms of their properties and combined with weighting mechanisms for balancing their contributions to the ranking. The use of visual and textual information in a single retrieval system sometimes limits its applicability due to the lack of modularity...

Images are ubiquitous in biomedicine and the image viewers play a central role in many aspects of modern health care. Tremendous amounts of medical image data are captured and recorded in digital format during the daily clinical practice, medical research, and education (in 2009, over 117,000 images per day in the Geneva radiology department alone). Facing such an unprecedented volume of image ...

One of the tools that will be essential for future electronic publishing is a powerful image retrieval system. The author should be able to search an image database for images that convey the desired information or mood; a reader should be able to search a corpus of published work for images that are relevant to his or her needs. Most commercial image retrieval systems associate keywords or tex...

p. 1 Exploring the Stability of IDF Term Weighting p. 10 Completely-Arbitrary Passage Retrieval in Language Modeling Approach p. 22 Semantic Discriminative Projections for Image Retrieval p. 34 Comparing Dissimilarity Measures for Content-Based Image Retrieval p. 44 A Semantic Content-Based Retrieval Method for Histopathology Images p. 51 Integrating Background Knowledge into RBF Networks for T...

We present an automated Image Annotation system called I-Tag which uses both visual and textual information of the images and recommends relevant tags for them. The automatic generation of metadata would allow image searches and content-based image retrieval (CBIR) to be more effective. We use state of the art tools on text based retrieval and image content based retrieval to retrieve similar i...

introduction: content based image retrieval (cbir) is a method of image searching and retrieval in a  database. in medical applications, cbir is a tool used by physicians to compare the previous and current  medical images associated with patients pathological conditions. as the volume of pictorial information  stored in medical image databases is in progress, efficient image indexing and retri...

Technology advances in the areas of Image processing IP and Information Retrieval IR have evolved separately for a long time However successful content based image retrieval systems require the integration of the two There is an urgent need to develop integration mechanisms to link the image retrieval model to text retrieval model such that the well established text retrieval techniques can be ...

Novel approaches are needed to support content-based retrieval on large-scale geographic image databases. In this paper, we present a new approach termed Keyblock for content-based geographic image retrieval, which is a generalization of the text-based information retrieval technology in the image domain. In this approach, methods for extracting comprehensive geographic image features are provi...

We propose a method for constructing a vector for a document image to represent its content to facilitate text retrieval. The method is based on an N-Gram algorithm for text similarity measure based on the frequency of occurrence of n-character strings appearing in the electronic text. Instead of using ASCII values, the present study investigates the use of character images to obtain the docume...

In the ImageCLEF 2005 campaign, the LIC2M participated in the ad hoc task, the medical task and the annotation task. For both ad hoc and medical task, we perform experiments on merging the results of two independent search systems: a crosslanguage information retrieval system exploiting the text part of the query and a content-based image retrieval system exploiting the example images given wit...