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...

Because of recent advances in graphics hardand software, both the production and use of 3D models are increasing at a rapid pace. As a result, a large number of 3D models have become available on the web, and new research is being done on 3D model retrieval methods. Query and retrieval can be done solely based on associated text, as in image retrieval, for example (e.g. Google Image Search [1] ...

Image retrieval till today is one of the most challenging problems in computer science. Even though there are lots of researches performed around the World, an efficient, user friendly image retrieval system still seems to be an unachievable goal. ImageCLEF Photo Retrieval Track allows to compare various approaches to this challenging problem. In this paper we present a staring point of our res...

We describe our approach to the ImageCLEF Photo and WikiMediaMM 2008 tasks. The novelty of our method consists of combining image segment based image retrieval with our text based approach. We rank text hits by our own Okapi BM25 based information retrieval system and image similarities by using a feature vector describing the visual content of image segments. Images were segmented by a home de...

Abstract One of the basic problems in the creating of the Realistic Image Databases (RIDB) structure is the efficient organization of the image retrieval. As a result of the analyses of the retrieval strategies we made, incl. GIS realistic images, we can make the conclusion that the solution of the problem for effective image retrieval is the approach for image sorting or indexing. Textand cont...

The search for appropriate data representations and visual features for content-based image retrieval continues within the computer vision community, alongside the development of new matching and indexing techniques to facilitate fast search in large-scale image databases. In this study, we present a solution to the problem of typeface identification and character recognition in text-based imag...

As the growth of digital image collections continues so does the need for efficient content based searching of images capable of providing quality results within a search time that is acceptable to users who have grown used text search engine performance. Some existing techniques, whilst being capable of providing relevant results to a user’s query will not scale up to very large image collecti...

Despite the explosion of text on the Internet, hard copy documents that have been scanned as images still play a significant role for some tasks. The best method to perform ranked retrieval on a large corpus of document images, however, remains an open research question. The most common approach has been to perform text retrieval using terms generated by optical character recognition. This pape...

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...

This paper describes the participation of the MIRACLE team at the ImageCLEF Photographic Retrieval task of CLEF 2008. We succeeded in submitting 41 runs. Obtained results from text-based retrieval are better than content-based as previous experiments in the MIRACLE team campaigns [5, 6] using different software. Our main aim was to experiment with several merging approaches to fuse text-based r...