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...

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...

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 ...

Efficient content-based image retrieval (CBIR) of biomedical images is a challenging problem. Feature representation algorithms used in indexing medical images on the pathology of interest have to address conflicting goals of reducing feature dimensionality while retaining important and often subtle biomedical features. In case of the vertebra, its shape effectively describes various pathologie...

Our work in content-based image retrieval (CBIR) relies on content-analysis of multiple representations of an image which we term multiple viewpoints or channels. The conceptual idea is to place each image in multiple feature spaces and then perform retrieval by querying each of these spaces and merging the several responses. We have shown that a simple realization of this strategy can be used ...

Content_based image retrieval is a promising approach because of its automatic indexing, recognition and retrieval. This paper is a contribution in the field of the content Based Image Retrieval (CBIR). Objects are represented by their outlines shapes (silhouettes) and described following the XLWDOS Textual Description (Larabi et al., 2003). Textual Descriptors are sensitive to noise. The autho...

In this paper we present a region growing approach for color images using an online learning algorithm that aims for content-based image retrieval systems. Our learning algorithm follows a variation of Bayesian estimation procedure to characterize each region as it is grown. The resulting image growing procedure is simple to implement, robust to initial parameters and has a linear complexity. R...

Content based image retrieval, a technique which uses visual contents of image to search images from large scale image databases according to users' interests. This paper provides a comprehensive survey on recent technology used in the area of content based face image retrieval. Nowadays digital devices and photo sharing sites are getting more popularity, large human face photos are available i...