Screening for refractive error with low-quality smartphone images

Zhongqi Yang, Eugene Yujun Fu, Grace Ngai, Hong Va Leong, Chi Wai Do, Lily Chan

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Uncorrected refractive errors can lead to permanent debilitating eye conditions if not corrected in a timely manner. Contemporary diagnostic methods rely on the professional acumen of optometrists and the use of expensive devices, which may not be easily accessible to all. According to the optical principle of photorefraction, refractive error can be estimated based on a relative pupil and crescent size of an eye image taken by a camera from a specified working distance. A low-cost approach would be to leverage smartphones with cameras for this purpose. However, the poor image quality generated from basic smartphones poses a challenge for the current approach as they often fail to accurately distinguish the crescent from the iris. We propose a novel method to detect and accurately measure the iris and crescent from smartphone photos. Based on this method, we further propose a set of features for machine learning to build our refractive error estimation model. The performance of our models are evaluated in an in-depth experiment.

Original languageEnglish
Title of host publication18th International Conference on Advances in Mobile Computing and Multimedia, MoMM2020 - Proceedings
EditorsPari Delir Haghighi, Ivan Luiz Salvadori, Matthias Steinbauer, Ismail Khalil, Gabriele Kotsis
PublisherAssociation for Computing Machinery
Pages119-128
Number of pages10
ISBN (Electronic)9781450389242
DOIs
Publication statusPublished - 30 Nov 2020
Event18th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2020, in conjunction with the 22nd International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2020 - Virtual, Online, Thailand
Duration: 30 Nov 20202 Dec 2020

Publication series

NameACM International Conference Proceeding Series

Conference

Conference18th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2020, in conjunction with the 22nd International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2020
CountryThailand
CityVirtual, Online
Period30/11/202/12/20

Keywords

  • compute-aided diagnosis
  • heathcare
  • machine learning
  • photorefraction
  • vision screening

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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