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Image pre-compensation to facilitate computer access for users with refractive errors

Published:01 September 2003Publication History

ABSTRACT

The use of computer technology for everyday tasks has become increasingly important in today's world. Frequently, computer technology makes use of Graphical User Interfaces (GUIs), presented through monitors or LCD displays. This type of visual interface is not well suited for users with visual limitations due to refractive errors, particularly when they are severe and not correctable by common means. In order to facilitate computer access for users with refractive deficiencies, an algorithm was developed, using a priori knowledge of the visual aberration, to generate an inverse transformation of the images that are then displayed on-screen, countering the effect of the aberration. The result is that when the user observes the screen displaying the transformed images, the image perceived in the retina will be similar to the original image. The algorithm was tested by artificially introducing a spherical aberration in the field of view of 14 subjects, totaling 28 individual eyes. Results show that when viewing the screen, this method of compensation improves the visual performance of the subjects tested in comparison to viewing uncompensated images.

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    • Published in

      cover image ACM Conferences
      Assets '04: Proceedings of the 6th international ACM SIGACCESS conference on Computers and accessibility
      October 2004
      202 pages
      ISBN:158113911X
      DOI:10.1145/1028630
      • cover image ACM SIGACCESS Accessibility and Computing
        ACM SIGACCESS Accessibility and Computing Just Accepted
        Sept. 2003 - Jan. 2004
        192 pages
        ISSN:1558-2337
        EISSN:1558-1187
        DOI:10.1145/1029014
        Issue’s Table of Contents

      Copyright © 2003 ACM

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      New York, NY, United States

      Publication History

      • Published: 1 September 2003

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      Acceptance Rates

      Assets '04 Paper Acceptance Rate25of47submissions,53%Overall Acceptance Rate436of1,556submissions,28%

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