[1]梁明明,沈柳笛,王伊雪,等.基于SVM的眼底血管分割技术[J].应用科技,2017,44(03):67-71.[doi:10.11991/yykj.201605020]
 LIANG Mingming,SHEN Liudi,WANG Yixue,et al.Eye fundus vessel segmentation technology based on SVM[J].yykj,2017,44(03):67-71.[doi:10.11991/yykj.201605020]
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基于SVM的眼底血管分割技术(/HTML)
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《应用科技》[ISSN:1009-671X/CN:23-1191/U]

卷:
第44卷
期数:
2017年03期
页码:
67-71
栏目:
计算机技术与应用
出版日期:
2017-06-05

文章信息/Info

Title:
Eye fundus vessel segmentation technology based on SVM
作者:
梁明明 沈柳笛 王伊雪 郑丽颖
哈尔滨工程大学 计算机科学与技术学院, 黑龙江 哈尔滨 150001
Author(s):
LIANG Mingming SHEN Liudi WANG Yixue ZHENG Liying
College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
关键词:
眼底图像血管分割高斯匹配滤波线检测器最佳匹配模板支持向量机均值漂移算法图像预分类
Keywords:
eye fundus imagesblood vessel segmentationGaussian matched filterlinear structure detectoroptimum matched templateSVMmean drifting algorithmimage preclassification
分类号:
TP399
DOI:
10.11991/yykj.201605020
文献标志码:
A
摘要:
针对眼底中小血管提取的问题,提出了一种基于支持向量机的眼底血管分割方法。首先,采用高斯匹配滤波器对眼底图像进行滤波,增强图像对比度;然后,为了加快滤波器的运算速度,提出一种改进的滤波方法,只需像素与最佳匹配模板做卷积;最后,为了提高算法的分类性能,采用均值漂移算法先对滤波后的图像预分类。仿真结果表明提出方法能更准确地分割出眼底血管网络,特别是对中小血管的分割更加精确。
Abstract:
An improved retinal vessel segmentation algorithm based on SVM was proposed to solve the problem that it is difficult to extract medium&small blood vessels at eye fundus.Firstly,the Gauss matched filter was used to filter retinal images and enhance the contrast ratio of images;then,in order to improve the efficiency of the filter,an improved method of Gaussian matched filter was put forward,which only needs the convolution of pixels and the optimum matching template;finally,in order to improve the classification performance of the algorithm,the mean drifting algorithm was used to preclassify the filtered image.The simulation results show that,by adopting the proposed method,the retinal vascular network can be segmented more accurately,especially,is is more accurate for the segment of medium&small blood vessels.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2016-5-26。
基金项目:国家自然科学基金项目(51679058).
作者简介:梁明明(1991-),男,硕士研究生;郑丽颖(1976-),女,教授,博士生导师.
通讯作者:郑丽颖,E-mail:2449624736@qq.com
更新日期/Last Update: 2017-07-07