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Abnormality detection in automated mass screening system of diabetic retinopathy

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4 Author(s)
Gang Luo ; Sch. of Electr. & Electron. Eng., Nanyang Technol. Inst., Singapore ; Opas Chutatape ; Huiqi Li ; S. M. Krishnan

An approach to abnormality detection from colour fundus images for an automated mass screening system is proposed in this paper, which uses the object-based colour difference image. Four colour models, viz. RGB, Luv, Lab and HVC, are evaluated based on hand-labelled feature maps, and Luv and Lab are selected for computing the colour difference because of their good performances in object classification. The object-based colour difference images of bright objects (e.g. exudates) and dark objects (e.g. haemorrhages and blood vessels) are obtained respectively according to the 2D histogram distribution on the L-u plane, and then a watershed transform is performed on the colour difference image to extract object candidates. A pre-thresholding and a post-verification procedure are performed to deal with the over-segmentation problem of the watershed transform

Published in:

Computer-Based Medical Systems, 2001. CBMS 2001. Proceedings. 14th IEEE Symposium on

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