The number of images on the World Wide Web has been increasing tremendously. Providing search services for images on the web has been an active research area. Web images are often surrounded by different associated texts like ALT text, surrounding text, image filename, html page title etc. Many popular internet search engines make use of these associated texts while indexing images and give hig...

Text extraction in real images taken in unconstrained environments remains surprisingly challenging in Computer Vision due to language characteristics, complex backgrounds and the text color. Extraction of text and caption from images and videos is important and in great demand for video retrieval, annotation, indexing and content analysis. In this paper we propose a weighted hybrid thresholdin...

Combining low-level features that represent the content of medical images with high level features that are saved with images would allow the expansion of text queries submitted to Content Based Image Retrieval (CBIR) systems. Expanding these text queries would allow CBIR systems to respond more effectively to specific queries when retrieving medical images. We hypothesized that adding an autom...

This paper presents a data model for images immersed in the world wide web and that derive their meaning from visual similarity, from the connection with the text of the pages that contains them, and from the link structure of the web. I will model images on the web as a graph whose nodes are either text documents or images, and whose edges are links, labeled with measures of relevance of one d...

We present an overview of a new paradigm for tackling long standing computer vision problems. Specifically our approach is to build statistical models which translate from a visual representations (images) to semantic ones (associated text). As providing optimal text for training is difficult at best, we propose working with whatever associated text is available in large quantities. Examples in...

We suggest a novel approach for compressing images of text documents based on building up a simple derived font from patterns in the image, and present the results of a prototype implementation based on our approach. Our prototype achieves better compression than most alternative systems, and the decompression time appears substantially shorter than other methods with the same compression rate....

The goal of a multimedia text extraction and recognition system is filling the gap between the already existing and mature technology of Optical Character Recognition and the new needs for textual information retrieval created by the spread of digital multimedia. A text extraction system from multimedia usually consists of the following four stages: spatial text detection, temporal text detecti...

In this paper, we propose a novel methodology for text detection in indoor/outdoor scene images. The proposed methodology is based on an efficient binarization and enhancement technique followed by a suitable connected component analysis procedure. Image binarization successfully process indoor/ outdoor scene images having shadows, non-uniform illumination, low contrast and large signal-depende...

Information retrieval is the task of nding documents, usually text, which are relevant to a user's information need. A conventional approach to information management of paper documents is normally based on classifying them into a hierarchical classiication structure. More recently we have seen electronic document management systems which manage scanned images of documents in the same way as pa...