one of the challenging issues in managing the existing large digital image libraries and databases is content based image retrieval (cbir). the accuracy of image retrieval methods in cbir is subject to effective extraction of image features such as color, texture, and shape. in this paper, we propose a new image retrieval method using contourlet transform coefficients to index texture of the im...

The purpose of this paper is to describe a methodology for enhancing search and retrieval of product information using content-based image retrieval in an electronic retailing application. Content-based image retrieval techniques have been applied to various applications such as medical information systems, environmental modeling, and satellite image analysis. Such techniques, however, can also...

This article describes the participation of the Image and Text Integration (ITI) group from the U.S. National Library of Medicine (NLM) in the ImageCLEF 2010 medical retrieval track. Our methods encompass a variety of techniques relating to document summarization and textand content-based image retrieval. Our text-based approaches utilize the Unified Medical Language System (UMLS) synonymy to i...

Content-based image retrieval (CBIR) has been an active research topic in the last decade. In this paper we proposed an image retrieval method using global and local features. Firstly, for local features extraction, SURF algorithm produces a set of interest points for each image and a set of 64-dimensional descriptors for each interest points and then to use Bag of Visual Words model, a cluster...

Image retrieval is a complex task that differs according to the context and the user requirements in any specific field, for example in a medical environment. Search by text is often not possible or optimal and retrieval by the visual content does not always succeed in modelling high-level concepts that a user is looking for. Modern image retrieval techniques consists of multiple steps and aim ...

This article describes the participation of the Communications Engineering Branch (CEB), a division of the Lister Hill National Center for Biomedical Communications, in the ImageCLEF 2011 medical retrieval track. Our methods encompass a variety of techniques relating to textand content-based image retrieval. Our textual approaches primarily utilize the Unified Medical Language System (UMLS) syn...