HCFeb 18, 2014

A Novel Approach for Canvas Accessibility Problem in HTML5

arXiv:1402.4410v1
Originality Incremental advance
AI Analysis

This addresses accessibility issues for vision-impaired web users, though it appears incremental as it builds on existing techniques like CBIR and extensions.

The paper tackled the problem of making HTML5 Canvas elements accessible to vision-impaired users by using content-based image retrieval and code mapping in a Firefox extension to replace Canvas with accessible HTML, achieving a solution that imposes no design rules on developers.

Canvas is a pixel-based inherently inaccessible element in HTML5.Therefore web users with vision disabilities cannot benefit from Canvas and its desired semantics and functionality. Regarding to the Canvas application in designing interactive graphical user interface, vision-impaired users may miss important information on web sites. This paper utilizes the content-based image retrieval (CBIR) technique as well as code mapping embedded in a Firefox extension to present a novel approach in order to make Canvas interactive user interface accessible. This extension replaces Canvas with an accessible equivalent HTML environment. Unlike previously done works on Canvas accessibility, the proposed approach does not impose any rules on developers and designers during Canvas design.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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