Extracting Blood Vessel in Sclera-Conjunctiva Image Based on Fuzzy C-means and modified Cone Responses

Please use this identifier to cite or link to this item: http://ir.lib.ncut.edu.tw/handle/987654321/6236

Title:	Extracting Blood Vessel in Sclera-Conjunctiva Image Based on Fuzzy C-means and modified Cone Responses
Authors:	林灶生
Contributors:	資訊工程系
Date:	2013-06
Issue Date:	2017-10-02 09:16:29 (UTC+8)
Abstract:	In this paper, we present a method of sclera-conjunctiva segmentation and blood vessel extraction to assist the doctor of traditional Chinese Medicine to diagnose patients. First, the color eye image was converted to grayscale image and clustered three classes using fuzzy c-means algorithm. Then the Sobel operator will be applied to detect the edges. Therefore, the sclera-conjunctiva region will be obtained using the morphological dilation, holes filling, and connectivity algorithm. Finally, a modified cone responses algorithm was proposed to extract the blood vessel from the sclera-conjunctiva.
Relation:	Lecture Notes in Artificial Intelligent
Appears in Collections:	[Department of Computer Science and Information Engineering] 【資訊工程系所】期刊論文

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