- From: Michael Vorburger <mike@vorburger.ch>
- Date: Thu, 3 Dec 1998 06:49:03 +0100
- To: <w3c-wai-er-ig@w3.org>, "Afzal Ballim" <ballim@di.epfl.ch>
- Cc: <perrocho@inf.ethz.ch>, <kennel@inf.ethz.ch>
Hello Here is finally the promised draft of the pager of my ALTifier project. You can download it from http://www.vorburger.ch/project/alt/ in Word, PDF or PS format. Sorry for no time for an HTML version of this draft. The abstract is given below. Notice that this is a draft, and one should frequently substitute "is" by "will be" ... ;-) All comment is welcome! Any pointers to libraries that might be usefull are of interest; especially a proxy server, a GIF & PNG comment extracting stuff, and a simple OCR API. Regards, Michael ---------------------------------------------------------------------------- ------------------ ABSTRACT of "ALTifier - Web Accessibility Enhancement Tool" full report at http://www.vorburger.ch/project/alt/ The goal of this project («ALTifier - Web Accessibility Enhancement Tool») was to research and implement tools to generate textual alternatives such as the ALT attribute in IMG and other graphical HTML elements. Often image and some other HTML tags lack a textual alternative. This makes them inaccessible to screen readers, non-visual/text-only browsers and braille readers. Adding alternate descriptions can make such pages more accessible. On one hand, the project focuses on HTML authors with an "author mode" tool to set ALT texts on a site-wide per-image basis, instead per each occurrence in HTML documents. The idea of this tool is motivate HTML authors to set ALT on all images by facilitating this job. On the other hand, for users surfing on existing sites with lack of ALT, a "user mode" tool tries to guess ALT text by heuristics. This tool is a proxy server which filters/transforms HTML and reads pages from the original Web server, inserts ALT, and sends them on to the Web client. The heuristics used to guess alternate text range from looking at an image's height & width, following links to extract a description from a document title, apply OCR to find text on buttons, to some simple natural language recognition. The project report gives a detailed description of the implementation and explains design choices. ---- Michael Vorburger <mike@vorburger.ch> & <michael.vorburger@epfl.ch> QUOTE: "Everything that does not kill you, makes you stronger." HOMEPAGE: http://www.vorburger.ch
Received on Thursday, 3 December 1998 00:47:33 UTC