[1]王玉亮,廖文和,沈建新,等.基于快速鲁棒特征的眼底图像自动配准与拼接[J].南京理工大学学报(自然科学版),2012,36(01):79-85.
 WANG Yu-liang,LIAO Wen-he,SHEN Jian-xin.Automatic Fundus Images Registration and Mosaic Based on Speeded up Robust Features[J].Journal of Nanjing University of Science and Technology,2012,36(01):79-85.
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基于快速鲁棒特征的眼底图像自动配准与拼接
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
36卷
期数:
2012年01期
页码:
79-85
栏目:
出版日期:
2012-02-29

文章信息/Info

Title:
Automatic Fundus Images Registration and Mosaic Based on Speeded up Robust Features
作者:
王玉亮; 廖文和; 沈建新;
南京航空航天大学机电学院;
Author(s):
WANG Yu-liangLIAO Wen-heSHEN Jian-xin
College of Mechanical & Electrical Engineering,Nanjing University of Aeronautics and Astronautics, Nanjing 210016,China
关键词:
快速鲁棒特征 图像配准 图像融合 图像拼接 眼底图像
Keywords:
speeded up robust features image registration image fusion image mosaic fundus images
分类号:
TP391.41
摘要:
针对眼底图像对比度低、光照不均匀、视场局限及不同视场间存在几何畸变等特点,提出一种基于快速鲁棒特征(SURF)的眼底图像自动配准与拼接算法。该算法分别提取各视场眼底图像同态滤波增强后有效视场的SURF,特征匹配后得到匹配点对,结合透视变换模型和RANSAC算法去除误匹配点对,周围视场依次与中央视场匹配计算变换矩阵,配准、融合后得到眼底全景图像。对项目中实际的眼底照相机获取图像的自动配准与拼接表明,该算法可以快速、高精度地实现不同视场眼底图像的自动配准与拼接,精度达到像素级,具有很好的鲁棒性。
Abstract:
In order to overcome the characteristics of low contrast,non-uniform illumination,limited field of view(FOV),and the geometric distortion between different FOVs of the fundus images,an automatic fundus image registration and mosaic algorithm based on speeded up robust features(SURF) is presented.Fundus images are enhanced by homomorphism filtering,and the SURF features in effective FOVs are extracted and described using vector to determine the matching feature point pairs between images.Outlier point pairs are rejected using RANSAC algorithm employing a perspective model,and transformation matrixes are computed according to the matching point pairs of surrounding FOV images to the central in turn,image registration and image fusion are implemented to get fundus panoramic image finally.The automatic registration and mosaic results of multiple FOV images obtained by fundus camera show that the algorithm is robust,the stability with registration accuracy reaches pixel level and the high-precision automatic fundus image mosaic can be achieved.

参考文献/References:

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备注/Memo

备注/Memo:
江苏省“333工程”(2007-16-59);江苏省科技支撑计划项目(BE2010652);南京航空航天大学专项科研(2010027)
更新日期/Last Update: 2012-10-12