Image pre-compensation for visually impaired computer users with variable pupil size Conference

Huang, J, Barreto, A, Alonso, M et al. (2013). Image pre-compensation for visually impaired computer users with variable pupil size . 151 LNEE 171-182. 10.1007/978-1-4614-3558-7_14

cited authors

  • Huang, J; Barreto, A; Alonso, M; Adjouadi, M

authors

abstract

  • Visual perception is one of the most important processes involved in human-computer interaction. However, many users with visual impairments may suffer from various visual aberrations which hamper their perception of the images displayed on the computer screen. To facilitate the interaction of these users with computers, the pre-compensation of computer images according to their particular visual aberration has been proposed. The pre-compensation process used is based on a priori knowledge of the visual aberration of the user's eye, which can be measured by a wavefront analyzer. Unfortunately, the visual aberration is measured for a specific pupil size. If the pupil size changes, the visual aberration is modified and, therefore, the pre-compensation model should also be modified, otherwise the efficiency of the pre-compensation method will be deteriorated. This paper presents a pre-compensation method that uses an algorithm to adapt the wavefront aberration function to a new pupil size if the wavefront aberration for a larger pupil size is known. Applying this algorithm, it is possible to keep the pupil size assumed for image pre-compensation matched to the effective pupil size of the user's eye during viewing. Preliminary tests are implemented with aberration data of a human eye through simulation. The results demonstrate that the image perceived after pre-compensation adjustment is better than the one without adjustment, verifying the capability of the resizing algorithm to adjust the pre-compensation model. © 2013 Springer Science+Business Media.

publication date

  • January 1, 2013

Digital Object Identifier (DOI)

start page

  • 171

end page

  • 182

volume

  • 151 LNEE