• DocumentCode
    1582686
  • Title

    Identification and segmentation of exudates using SVM classifier

  • Author

    Ruba, T. ; Ramalakshmi, K.

  • Author_Institution
    Dept. of ECE, P.S.R. Eng. Coll., Sivakasi, India
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The eye is a vital organ and it is the main organ that is mainly affected because of diabetes. Different types of diseases were commonly present in an eye. The exudate detection in retinal images will be helpful in the early identification of Diabetic Retinopathy. The retinal images were initially resized, and they are filtered using median filter. Then the filtered image is classified into Normal or exudates affected by using the SVM classifier. The Gabor features and GLCM features were provided to the SVM classifier for classifying retinal images into normal (or) abnormal. The exudates were segmented using thresholding and morphological operations. The performance of the process is measured by calculating the performance metrics of the classifier such as Correctness, Sensitivity, Specificity.
  • Keywords
    Gabor filters; feature extraction; image segmentation; median filters; retinal recognition; support vector machines; GLCM features; Gabor features; SVM classifier; diabetic retinopathy; exudate detection; eye; median filter; retinal images; vital organ; Blood vessels; Diabetes; Feature extraction; Gabor filters; Image segmentation; Retina; Support vector machines; Diabetic retinopathy; Exudates; GLCM; Gabor; SVM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on
  • Conference_Location
    Coimbatore
  • Print_ISBN
    978-1-4799-6817-6
  • Type

    conf

  • DOI
    10.1109/ICIIECS.2015.7193219
  • Filename
    7193219