Detection and Classification of Early Stage Lesions in Diabetic Retinopathy using Color Fundus Images
S.Sudha1, A.Srinivasan2, T.Gayathri Devi3
1S.Sudha, Department of ECE ,School of EEE, SRC, SASTRA Deemed University, Kumbakonam, Tamilnadu, India.
2A.Srinivasan, Department of ECE ,School of EEE, SRC, SASTRA Deemed University, Kumbakonam, Tamilnadu, India.
3T.Gayathri Devi, Department of ECE ,School of EEE, SRC, SASTRA Deemed University, Kumbakonam, Tamilnadu, India.
Manuscript received on 01 August 2019. | Revised Manuscript received on 07 August 2019. | Manuscript published on 30 September 2019. | PP: 4476-4480 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6806098319/2019©BEIESP | DOI: 10.35940/ijrte.C6806.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Detection of lesions and classification of Diabetic Retinopathy (DR) play an important role in day-to-day life. In this proposed system, colour fundus image is pre-processed using morphological operations to recover from noises and it is converted into HSV colorspace. Fuzzy C-Means Clustering algorithm (FCMC) is used for segmenting the early stage lesions such as Microaneurysms (Ma), Haemorrhages (HE) and Exudates. Hybrid features such as colour correlogram and speeded up robust features (surf) are extracted to train the classifier. Cascaded Rotation Forest (CRF) classifier is used for classification of diabetic retinopathy. The proposed system increases the accuracy of detection and it has got high sensitivity.
Keywords- Diabetic Retinopathy (DR); Microaneurysms (Ma); Haemorrhages (HE); Exudates; morphological operations; Fuzzy C-Means Clustering algorithm (FCMC);Cascaded Rotation Forest (CRF) classifier.
Scope of the Article: Classification