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Journal of Intelligent Systems and Internet of Things

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Journal of Intelligent Systems and Internet of Things

Volume 17 , Issue 1 , PP: 177-195, 2025 | Cite this article as | XML | Html | PDF | Full Length Article

A Novel IoT based Wavelet and PCA Approach for Improved Glaucoma Classification Using Retinal Images

Vivek Jain 1 * , H. Shree Kumar 2 , Hemant Sharma 3 , R. Kiran Kumar 4 , Chandrasekaran Raja 5 , Krishna Kishore Thota 6

  • 1 Asst. Professor, Department of ECE, Madanapalle Institute of Technology & Science, MITS, Madanapalle, India - (vivekjain21979@gmail.com)
  • 2 Asst. Professor, Department of ECE, Madanapalle Institute of Technology & Science, MITS, Madanapalle, India - (hshreekumar@gmail.com)
  • 3 Department of Computer Science & Engineering, IES College of Technology, Bhopal, Madhya Pradesh, 462044, India - (hemant.research@iesuniversity.ac.in)
  • 4 Asst. Professor, Department of ECE, Madanapalle Institute of Technology & Science, MITS, Madanapalle, India - (royalkiran406@gmail.com)
  • 5 Associate Professor, Department of ECE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India - (drrajac@veltech.edu.in)
  • 6 Asst. Professor, Department of CSE (Honors), Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, AP, India - ( tkrishnakishore@kluniversity.in)

    • Doi: https://doi.org/10.54216/JISIoT.170113

    Received: January 29, 2025 Revised: March 03, 2025 Accepted: April 16, 2025
    Abstract

    The proposed research implements a new 3D-block-based alpha-rooting enhancement method, which uses PCA classification for detecting glaucoma. The use of Euclidean distance in current image enhancement methods tends to lose important structural details that result in incorrect classification outcomes. The proposed method executes block-matching and grouping operations to locate equivalent 3D patterns before using adaptive alpha-rooting adjustment, which automatically controls contrast throughout optic disc and optic cup regions. Following enhancement processing an additional polishing stage optimizes these results for classification purposes. The classification of enhanced images takes place using PCA and its wavelet variants to extract important retinal features. The proposed system utilizes both ACRIMA dataset and real-world hospital images to show better classification achievements than CLAHE-based enhancement while validating its effectiveness. The experimental outcome demonstrated both high accuracy and reduced time consumption when using biorthogonal DWT with (2D) ²-PCA for classification. The proposed method offers a time-effective hardware-oriented solution for automatic glaucoma detection by combining conventional statistical techniques with deep learning-based classification approaches. The method provides clinical facilities with a dependable standard for glaucoma identification and diagnosis improvement. The Proposed 3D block-based adaptive alpha rooting method achieves a total accuracy level of 95.1%. The U-net model achieves 91.0% accuracy while CNN reaches 90.3% and RF delivers 87.1%. At the same time, SVM provides 86.3% accuracy while PCA returns 85.2% and DWT reaches 84.2% and KNN establishes 81.2% accuracy.

    Keywords :

    SVM , MRI , CNN , PCA , DWT , IoT , PAT , ACRIMA , CAD

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    Cite This Article As :
    Jain, Vivek. , Shree, H.. , Sharma, Hemant. , Kiran, R.. , Raja, Chandrasekaran. , Kishore, Krishna. A Novel IoT based Wavelet and PCA Approach for Improved Glaucoma Classification Using Retinal Images. Journal of Intelligent Systems and Internet of Things, vol. , no. , 2025, pp. 177-195. DOI: https://doi.org/10.54216/JISIoT.170113
    Jain, V. Shree, H. Sharma, H. Kiran, R. Raja, C. Kishore, K. (2025). A Novel IoT based Wavelet and PCA Approach for Improved Glaucoma Classification Using Retinal Images. Journal of Intelligent Systems and Internet of Things, (), 177-195. DOI: https://doi.org/10.54216/JISIoT.170113
    Jain, Vivek. Shree, H.. Sharma, Hemant. Kiran, R.. Raja, Chandrasekaran. Kishore, Krishna. A Novel IoT based Wavelet and PCA Approach for Improved Glaucoma Classification Using Retinal Images. Journal of Intelligent Systems and Internet of Things , no. (2025): 177-195. DOI: https://doi.org/10.54216/JISIoT.170113
    Jain, V. , Shree, H. , Sharma, H. , Kiran, R. , Raja, C. , Kishore, K. (2025) . A Novel IoT based Wavelet and PCA Approach for Improved Glaucoma Classification Using Retinal Images. Journal of Intelligent Systems and Internet of Things , () , 177-195 . DOI: https://doi.org/10.54216/JISIoT.170113
    Jain V. , Shree H. , Sharma H. , Kiran R. , Raja C. , Kishore K. [2025]. A Novel IoT based Wavelet and PCA Approach for Improved Glaucoma Classification Using Retinal Images. Journal of Intelligent Systems and Internet of Things. (): 177-195. DOI: https://doi.org/10.54216/JISIoT.170113
    Jain, V. Shree, H. Sharma, H. Kiran, R. Raja, C. Kishore, K. "A Novel IoT based Wavelet and PCA Approach for Improved Glaucoma Classification Using Retinal Images," Journal of Intelligent Systems and Internet of Things, vol. , no. , pp. 177-195, 2025. DOI: https://doi.org/10.54216/JISIoT.170113

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