Recent research advances in text detection allow us for finding text regions in natural scenes rather accurately. Global features in Content-Based Image Retrieval,however, typically do not cover such a high level information. While characteristics of text regions may be reflected by texture or color properties, the respective pixels are not treated in a different way. In this work we investigat...

This working notes describe the runs and results obtained by the LIG at ImageCLEFphoto 2008. The submitted runs are: two runs (text only and text+image) without diversification on classes, and two runs (text only and text+image) with class diversification were submitted. The text retrieval is based on language model of Information Retrieval, and the image part is processed using RGB histograms ...

Image annotation provides several keywords automatically for a given image based on various tags to describe its contents which is useful in Image retrieval. Various researchers are working on text based and content based image annotations [7,9]. It is seen, in traditional Image annotation approaches, annotation words are treated equally without considering the importance of each word in real w...

Cross-modal remote sensing text-image retrieval (RSCTIR) has recently become an urgent research hotspot due to its ability of enabling fast and flexible information extraction on (RS) images. However, current RSCTIR methods mainly focus global features RS images, which leads the neglect local that reflect target relationships saliency. In this article, we first propose a novel framework based (...

As the number of images grows rapidly on the Internet, the scalability of image retrieval systems becomes a significant issue. In this paper, we propose two distributed clustering algorithms to scale up the bag-ofvisual-words model on millions of images and billions of visual features by leveraging distributed systems. We also introduce a multimodal fusion model to utilize textual data to impro...

In a high-level semantic retrieval process, we utilize the search engine to retrieve a large number of images using a given text-based query. In a low-level image retrieval process, the system provides a similar image search function for the user to update the input query for image similarity characterization. This paper presents an On-line Content-Based Image Retrieval System using joint query...

Arisingout of interest inapproaches for content-based image retrieval from theHST image archive, we prototyped free text retrieval systems using accepted proposal abstracts (hence: what the later associated images were meant to deal with). Other possible applications of such free text retrieval systems in observatory operations are described. Weusedwidely available, publicly accessible, (Sun) U...

introduction Content-based image retrieval (CBIR) has wide applications in public life. Either from a static image database or from the Web, one can search for a specific image, generally browse to make an interactive choice, and search for a picture to go with a broad story or to illustrate a document. Although CBIR has been well studied, it is still a challenging problem to search for images ...