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Automated Improved Blood Vessels Detection Using Morphological Processing, DWT, and Gamma Correction Method

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Proceedings of International Conference on Advanced Computing Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1406))

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Abstract

Retinal image processing is one of the growing fields of research in medical image processing domain in modern days. Blood vessels detection plays an important role for detection of retinal diseases such as diabetic retinopathy. This research paper suggests an automatic method for blood vessels detection using some morphological processing, DWT, and gamma correction that can be used to detect diabetic retinopathy in later stages. Due to noise, non-uniform illuminations, camera shake of fundus camera, low contrast, etc., detection of vessels is noise-prone and inaccurate. To reduce the non-uniform luminance of the retinal image, discrete wavelet transform (DWT) is used as preprocessing method before segmenting the blood vessels. To enhance the contrast of the retinal image, gamma correction is used. After that some morphological operations are performed on the retinal image after preprocessing to detect and segment the blood vessels. Three different experiments are carried out here: directly applying morphological operations to detect vessels from retinal fundus image of Diaretdb1 database, application of DWT with morphological operations for vessels detection and combined application of DWT, and gamma corrections integrated with morphological operations. It is found that the performance of the automated proposed method is better compared to other two approaches.

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Authors and Affiliations

  1. Department of ECE, Kalyani Government Engineering College, Kalyani, West Bengal, India

    Amritayan Chatterjee & Himadri Sekhar Dutta

Authors
  1. Amritayan Chatterjee
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  2. Himadri Sekhar Dutta
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal, India

    Jyotsna Kumar Mandal

  2. School of Computing and Information Systems, The University of Melbourne, Melbourne, VIC, Australia

    Rajkumar Buyya

  3. Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, West Bengal, Kolkata, West Bengal, India

    Debashis De

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Chatterjee, A., Dutta, H.S. (2022). Automated Improved Blood Vessels Detection Using Morphological Processing, DWT, and Gamma Correction Method. In: Mandal, J.K., Buyya, R., De, D. (eds) Proceedings of International Conference on Advanced Computing Applications. Advances in Intelligent Systems and Computing, vol 1406. Springer, Singapore. https://doi.org/10.1007/978-981-16-5207-3_50

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