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Retinal Image Quality Assessment Using Sharpness and Connected Components

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Computer Vision and Image Processing (CVIP 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1568))

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Abstract

Mobile application based diagnosis has become an aid nowadays. For better diagnosis, the quality of image needs to be good. Automatic assessment of images will help the ophthalmologists to focus more on the diagnosis. To assist the experts, an automated retinal image quality assessment method has been proposed. The proposed method make use of the features extracted from the sharpness and connected components of the fundus image. In particular, the image is divided into patches and the features are extracted. Those extracted features are used to train a machine learning model. The proposed model has achieved comparable results on the private dataset and outperformed the existing methods on public datasets.

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Authors and Affiliations

  1. Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram, Chennai, India

    S. Kiruthika & V. Masilamani

Authors
  1. S. Kiruthika
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  2. V. Masilamani
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Corresponding author

Correspondence to S. Kiruthika .

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Editors and Affiliations

  1. Indian Institute of Technology Roorkee, Roorkee, India

    Balasubramanian Raman

  2. Indian Institute of Technology Ropar, Ropar, India

    Subrahmanyam Murala

  3. Jadavpur University, Kolkata, India

    Ananda Chowdhury

  4. Indian Institute of Technology Ropar, Ropar, India

    Abhinav Dhall

  5. Indian Institute of Technology Ropar, Ropar, India

    Puneet Goyal

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Kiruthika, S., Masilamani, V. (2022). Retinal Image Quality Assessment Using Sharpness and Connected Components. In: Raman, B., Murala, S., Chowdhury, A., Dhall, A., Goyal, P. (eds) Computer Vision and Image Processing. CVIP 2021. Communications in Computer and Information Science, vol 1568. Springer, Cham. https://doi.org/10.1007/978-3-031-11349-9_16

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  • DOI: https://doi.org/10.1007/978-3-031-11349-9_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-11348-2

  • Online ISBN: 978-3-031-11349-9

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