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Handbook of Multimedia Information Security: Techniques and Applications pp 359–375Cite as

Image Processing Based Automated Glaucoma Detection Techniques and Role of De-Noising: A Technical Survey

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Abstract

This chapter presents a detailed study of the image processing steps to identify glaucoma including the key role of the de-noising in the detection of Glaucoma. De-noising plays an important role in the area of medical imaging. One of the major applications of image processing is detection of retinal diseases. Further, important diagnostic parameters to detect glaucoma are discussed in detail. Several techniques with different diagnostic parameters are used to detect glaucoma. Image acquisition is the first step in this detection process. Existing noise in the medical image may degrade the accuracy of the detection. Therefore a preprocessing step is highly required before the commencement of actual processing. In general, optical coherence tomography (OCT) and Ultrasound retinal image are corrupted by speckle noise. The speckle noise removal techniques are reviewed. The popular de-speckling approaches are classified into different groups and a brief overview is provided. The application of these de-noising methods outperforms in diagnosing the progression of glaucoma.

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Acknowledgement

This chapter is a part of my Ph.D. thesis which has been submitted to AKTU, Lucknow.

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Authors and Affiliations

  1. Dr. A. P. J. Abdul Kalam Technical University, Lucknow, Uttar Pradesh, India

    Sima Sahu

  2. Department of Electronics, Kamla Nehru Institute of Technology (KNIT), Sultanpur, Uttar Pradesh, India

    Harsh Vikram Singh

  3. Department of ECE, Motilal Nehru NIT, Allahabad, Prayagraj, India

    Basant Kumar

  4. Department of Computer Science and Engineering, NIT Patna, Patna, India

    Amit Kumar Singh & Prabhat Kumar

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  1. Sima Sahu
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Editors and Affiliations

  1. Department of Computer Science and Engineering, NIT Patna, Patna, India

    Amit Kumar Singh

  2. Department of Electronics Engineering, Indian Institute of Technology, BHU, Varanasi, Uttar Pradesh, India

    Anand Mohan

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Sahu, S., Singh, H.V., Kumar, B., Singh, A.K., Kumar, P. (2019). Image Processing Based Automated Glaucoma Detection Techniques and Role of De-Noising: A Technical Survey. In: Singh, A., Mohan, A. (eds) Handbook of Multimedia Information Security: Techniques and Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-15887-3_16

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  • DOI: https://doi.org/10.1007/978-3-030-15887-3_16

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