Genetic based Fuzzy Seeded Region Growing Segmentation for diabetic retinopathy images

Segmentation is an important task for image analysis. Region based segmentation methods are best suited for images taken in noisy environment. Selecting a seed pixel is a challenging task in region growing methods. To overcome this drawback, Genetic based Fuzzy Seeded Region Growing Segmentation (GF...

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Bibliographic Details
Published in2013 International Conference on Computer Communication and Informatics pp. 1 - 5
Main Authors Tamilarasi, M., Duraiswamy, K.
Format Conference Proceeding Journal Article
LanguageEnglish
Published IEEE 01.01.2013
Subjects
Algorithms
Computers
Conferences
Diabetes
Diabetic retinopathy
Educational institutions
Fuzzy
Fuzzy clustering
Genetic algorithm
Genetics
Image edge detection
Image segmentation
Pixels
Region growing
Retina
Retinopathy
Segmentation
Tasks
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ISBN1467329061
9781467329064
DOI10.1109/ICCCI.2013.6466117

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Summary:Segmentation is an important task for image analysis. Region based segmentation methods are best suited for images taken in noisy environment. Selecting a seed pixel is a challenging task in region growing methods. To overcome this drawback, Genetic based Fuzzy Seeded Region Growing Segmentation (GFSRGS) algorithm is proposed in this paper. The proposed algorithm optimizes the selection of multiple seed pixels using genetic based fuzzy approach. It is experimented with diabetic retinopathy images to find out the exudates regions. The results of the proposed algorithm are compared with the ground truth data. It achieves better accuracy when compared to the existing methods.
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ISBN:1467329061
9781467329064
DOI:10.1109/ICCCI.2013.6466117