How to Analyze Imagetexts

2000

Proceedings of the Fourth International Conference on Document Analysis and Recognition, 1997

This paper describes a document image analysis toolbox, including a collection of document image processing and analysis algorithms, performance metrics and evaluation tools, and graphical model tools for information integration.

1994

Our research explores the interaction of textual and photographic information in document understanding. Speci cally, we have been working on a computational model whereby textual captions are used as collateral information in the interpretation of the corresponding photographs. The nal understanding of the picture and caption re ects a consolidation of the information obtained from each of the two sources and can thus be used in intelligent information retrieval tasks. The problem of performing general-purpose vision without a priori knowledge is very di cult at best. The concept of using collateral information in scene understanding has been explored in systems that use general scene context in the task of object identi cation. The work described here extends this notion by incorporating picture speci c information. A multi-stage system PICTION which uses captions to identify humans in an accompanying photograph is described.

2001

Reference Word Count: 338

1995

The conversion of documents into electronic form has proved more difficult than anticipated. Document image analysis still accounts for only a small fraction of the rapidly-expanding document imaging market. Nevertheless, the optimism manifested over the last thirty years has not dissipated. Driven partly by document distribution on CD-ROM and via the World Wide Web, there is more interest in the preservation of layout and format attributes to increase legibility (sometimes called "page reconstruction") rather than just text/non-text separation. The realization that accurate document image analysis requires fairly specific pre-stored information has resulted in the investigation of new data structures for knowledge bases and for the representation of the results of partial analysis. At the same time, the requirements of downstream software, such as word processing, information retrieval and computer-aided design applications, favor turning the results of the analysis and recognition into some standard format like SGML or DXF. There is increased emphasis on large-scale, automated comparative evaluation, using laboriously compiled test databases. The cost of generating these databases has stimulated new research on synthetic noise models. According to recent publications, the accurate conversion of business letters, technical reports, large typeset repositories like patents, postal addresses, specialized line drawings, and office forms containing a mix of handprinted, handwritten and printed material, is finally on the verge of success.

2021

Nowadays, communication is a basic need in our society. However, some people cannot use the typical methods of communication for reasons that don't depend on them. A way of communication for those people is using pictograms. However, for people without specific training, understanding sentences formed by those pictograms is not easy, if not impossible. That's why tools that translate sentences written with pictograms into natural language are essential. Pict2Text 1.0 is the only existing tool that translates messages written with pictograms to natural language (Spanish). Unfortunately, it still has to be improved. One of the biggest flaws of the tool is the fact that the message with pictograms has to be created manually by looking for each pictogram in the search engine provided by the application. At this current state, the people who most need the tool can't use it because they would not be able to type the words to compound the message to select the pictograms. For t...

1995

In the late 1980's, the prevalence of fast computers, large computer memory, and inexpensive scanners fostered an increasing interest in document image analysis. With many paper documents being sent and received via fax machines and being stored digitally in large document databases, the interest grew to do more with these images than simply view and print them.

1997

This paper describes the Document Image Understanding Toolbox currently under development at the University of Washington's Intelligent Systems Laboratory The Toolbox provides a common data structure and a variety of document image analysis and understanding algorithms from which Toolbox users can construct document image processing systems. An algon'thms for font attribute recognition based on the image analysis techniques available in the toolbox ISL DIU Toolbox is also presented.

Ijca Proceedings on National Conference on Recent Trends in Computing, 2012