Detection Of Hard Exudates In Color Fundus Images Based On ELM Classifier

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@article{1701971,
      author = {Alaimahal A, Dr. S. Vasuki},
      title = {Detection Of Hard Exudates In Color Fundus Images Based On ELM Classifier},
      journal = {Iconic Research And Engineering Journals},
      year = {2020},
      volume = {3},
      number = {9},
      pages = {15-18},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1701971.pdf},
      abstract = {Diabetic Retinopathy is an eye disease caused due to diabetes complication. It leads to vision loss if not diagnosed at early stage. It can be assessed by detecting the hard exudates present in the color fundus images. The proposed methodology has two stages such as detection of hard exudates and classification of severity stages of diabetic retinopathy. A feature extraction technique is used to capture the global features like intensity, color and texture features. It is very useful to categorize the normal and abnormal images. In this, the detection of hard exudates is done by using ELM classifier. Classification of disease severity stages is assessed by using regional property of the hard exudates in the retinal image. The proposed detection performance has a sensitivity of 99% with specificity between 85% and 96%.},
      keywords = {Diabetic Retinopathy, Hard exudates, Discrete wavelet transform, Extreme Learning Machine Classifier.},
      month = {March},
  }