Volume 14Issue 3
May 2021
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CAI Huai-yu, SHI Yu, LOU Shi-liang, WANG Yi, CHEN Wen-guang, CHEN Xiao-dong. Pupil location algorithm applied to infrared ophthalmic disease detection[J]. Chinese Optics, 2021, 14(3): 605-614. doi: 10.37188/CO.2020-0170
Citation: CAI Huai-yu, SHI Yu, LOU Shi-liang, WANG Yi, CHEN Wen-guang, CHEN Xiao-dong. Pupil location algorithm applied to infrared ophthalmic disease detection[J].Chinese Optics, 2021, 14(3): 605-614.doi:10.37188/CO.2020-0170

Pupil location algorithm applied to infrared ophthalmic disease detection

doi:10.37188/CO.2020-0170
Funds:Supported by National Key R&D Program of China (No. 2017YFC0109901); Natural Science Foundation Project of Tianjin (No. 15JCQNJC14200)
More Information
  • Corresponding author:yushi_821@tju.edu.cn
  • Received Date:25 Sep 2020
  • Rev Recd Date:09 Nov 2020
  • Available Online:05 Feb 2021
  • Publish Date:14 May 2021
  • In order to quickly, accurately and automatically locate a pupil in ophthalmic disease detection, a location algorithm for a pupil’s center based on radial symmetry transformation was proposed. Firstly, the gray integral projection method combined with the maximum class square error method was used to complete the rough segmentation of human eye image, and a Region Of Interest (ROI) solely containing the pupil was extracted according to multi-lump screening conditions. Then the search radius range was set by using a minimum circumscribed rectangle on the ROI combined with gray-level morphological linear filtering. Finally, the pupil center was located using an improved radial symmetry transformation algorithm. The experimental results show that the location error of this algorithm is less than 8 pixels and the average processing time is 0.366 s. It can adapt to a large number of irrational states such as noise interference and an incomplete collection of human eye images and meets the pupil location performance requirements for many kinds of infrared ophthalmology disease detection equipment.

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