Evaluation of retrieval performance is a crucial problem in content-based image retrieval (CBIR). Many di erent methods for measuring the performance of a system have been created and used by researchers. This article discusses the advantages and shortcomings of the performance measures currently used. Problems such as de ning a common image database for performance comparisons and a means of g...

This paper presents the approaches used by the MIRACLE team to image retrieval at ImageCLEF 2005. Text-based and content-based techniques have been tested, along with combination of both types of methods to improve image retrieval. The text-based experiments defined this year try to use semantic information sources, like thesaurus with semantic data or text structure. On the other hand, content...

DCU participated in the ImageCLEF 2008 photo retrieval task, which aimed to evaluate diversity in Image Retrieval, submitting runs for both the English and Random language annotation conditions. Our approaches used text-based and image-based retrieval to give baseline runs, with the the highest-ranked images from these baseline runs clustered using K-Means clustering of the text annotations, wi...

This paper describes the participation of UAIC team at the ImageCLEF 2011 competition, Wikipedia Retrieval task. The aim of the task was to investigate retrieval approaches in the context of a large and heterogeneous collection of images and their noisy text annotations. We submitted a total of six runs, focusing our effort along the textual retrieval, query expansion on English language, combi...

The number of digital images is rapidly increasing, prompting the necessity for efficient image storage and retrieval systems. The management and the indexing of these large image and information repositories are becoming increasingly complex. Therefore, tools for efficient archiving, browsing and searching images are required. A straightforward way of using the existing information retrieval t...

Keyblock, which is a new framework we proposed for the contentbased image retrieval, is a generalization of the text-based information retrieval technology in the image domain. In this framework, keyblocks, which are analogous to keywords in text document retrieval, can be constructed by exploiting a clustering approach. Then an image can be represented as a list of keyblocks similar to a text ...

In this paper, we present our solutions for the WikipediaMM task at ImageCLEF 2008. The aim of this task is to investigate effective retrieval approaches in the context of a large-scale and heterogeneous collection of Wikipedia images that are searched by textual queries (and/or sample images and/or concepts) describing a user’s information need. We first experimented with a text-based image re...

Since the development of the first text-based image search on the internet, the area of image retrieval has come a long way to sophisticated content based image retrieval systems. On the other hand, the semantic gap causes that it is still not possible to create a system which can correctly identify any object in the image. However, this paper proposes a solution for classifying the one sort of...

The emergence of multimedia technology and the rapidly expanding image collections on the Internet have attracted significant research efforts in providing tools for effective retrieval and management of visual data. The need to find a desired image from a large collection is shared by many professional groups, including journalists, design engineers and art historians. Difficulties faced by te...

in this paper we propose novel algorithms for retrieving dental images from databases by their contents. based on special information of dental images, for better content based dental image retrieval and representation, the image attributes are used. we propose disr (dental image segmentation and retrieval), a content-based image retrieval method which is robust to translation and scaling of th...