Content-Based Image Retrieval (CBIR) locates, retrieves and displays images alike to one given as a query, using a set of features. It demands accessible data in medical archives and from medical equipment, to infer meaning after some processing. A problem similar in some sense to the target image can aid clinicians. CBIR complements text-based retrieval and improves evidence-based diagnosis, a...

Rapid growth of World Wide Web has increased the interest towards image retrieval. Different groups need to find a desired image from a collection. The users may require access to the images, based on primitive features, such as color, texture or shape, or associated text. The technology to access these images has also accelerated phenomenally. The current approaches are broad and inter-discipl...

Traditional computer-based image retrieval techniques provide several mechanisms to retrieve images. Generally, there are two major approaches being used in image retrieval systems. The first approach is content-based image retrieval which aims to retrieve images based on their visual criteria. This approach typically utilizes visual features, such as color, shape, texture, and layout, to deter...

Most of the currently available image database systems provide a text-based retrieval function called keyword retrieval, where users specify `keywords' such as titles, attributes, and categories of themes. But many times it is not easy for users to specify suitable keywords for a particular retrieval. Besides, building a large image database with complete description of contents is a very dicu...

A patent always contains some images along with the text. Many text based systems have been developed to search the patent database. In this paper, we describe PATSEEK that is an image based search system for US patent database. The objective is to let the user check the similarity of his query image with the images that exist in US patents. The user can specify a set of key words that must exi...

Current image retrieval techniques have shortcomings that make it difficult to search for images based on a semantic understanding of what the image is about. Since an image is normally associated with multiple contexts (e.g. when and where a picture was taken,) the knowledge of these contexts can enhance the quantity of semantic understanding of an image. In this paper, we present a context-aw...

The Image retrieval plays a key role in day-to-days world. This work is a review of various references of various image retrieval methods. This paper starts with discussing the working conditions of text based image retrieval then the content-based retrieval: patterns of use, levels, the role of semantics, and the semantic gap. We briefly discuss about various techniques of content based image ...

In this article, we describe the used technologies and experimental results for the medical retrieval task at ImageCLEF 2005. The topics of competition this year contain both semantic queries and visual queries. The content-based approach containing four image features and the text-based approach using word expansion are developed to accomplish the mission. The experimental results show that th...

This paper present the participation details of DEMIR (Dokuz Eylul University Multimedia Information Retrieval) research team at ImageCLEFwiki2011. This year we investigate on evaluating of different weighting models on text retrieval performance. In the case of low-level feature selection, we extracted different features and examined their performance to choose the proper feature for our exper...