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A Computationally Efficient Retina Detection and Enhancement Image Processing Pipeline for Smartphone-Captured Fundus Images

Abstract : 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 angiography-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 the five image processing components of 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 less than 1 second.
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https://hal-upec-upem.archives-ouvertes.fr/hal-01796763
Contributor : Yaroub Elloumi <>
Submitted on : Tuesday, May 22, 2018 - 1:58:31 AM
Last modification on : Thursday, October 22, 2020 - 3:02:02 PM
Long-term archiving on: : Tuesday, September 25, 2018 - 2:29:57 PM

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  • HAL Id : hal-01796763, version 1

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Yaroub Elloumi, Mohamed Akil, Nasser Kehtarnavaz. A Computationally Efficient Retina Detection and Enhancement Image Processing Pipeline for Smartphone-Captured Fundus Images. Journal of Multimedia Information System, Korea Multimedia Society, In press. ⟨hal-01796763⟩

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