Journal of Multimedia Information System

한국멀티미디어학회 (Korea Multimedia Society)
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A Computationally Efficient Retina Detection and Enhancement Image Processing Pipeline for Smartphone-Captured Fundus Images

  • Elloumi, Yaroub (Gaspard Monge Computer Science Laboratory, ESIEE-Paris, University Paris-Est Marne-la-Vallee) ;
  • Akil, Mohamed (Gaspard Monge Computer Science Laboratory, ESIEE-Paris, University Paris-Est Marne-la-Vallee) ;
  • Kehtarnavaz, Nasser (Department of Electrical and Computer Engineering, University of Texas at Dallas)
  • 투고 : 2018.04.28
  • 심사 : 2018.05.10
  • 발행 : 2018.06.30
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초록

Due to the handheld holding of smartphones and the presence of light leakage and non-balanced contrast, the detection of the retina area in smartphone-captured fundus images is more challenging than retinography-captured fundus images. This paper presents a computationally efficient image processing pipeline in order to detect and enhance the retina area in smartphone-captured fundus images. The developed pipeline consists of five image processing components, namely point spread function parameter estimation, deconvolution, contrast balancing, circular Hough transform, and retina area extraction. The results obtained indicate a typical fundus image captured by a smartphone through a D-EYE lens is processed in 1 second.

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참고문헌

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