Retinal Image Registration Using Geometrical Features
Retinal Image Registration Using Geometrical Features
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DOI：
10.1007/s10278-012-9501-7
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发表时间：
2013-04-01
影响因子：
4.4
通讯作者：
Sedaaghi, Mohammad Hossein
中科院分区：
文献类型：
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作者：
Gharabaghi, Sara;Daneshvar, Sabalan;Sedaaghi, Mohammad Hossein
在这项研究中，我们介绍了一种精确的视网膜图像配准方法，利用仿射不变矩（AMI）的形状描述符。首先，在参考图像和感测图像中提取一些闭合边界区域。然后，针对这些区域中的每一个计算AMI。选取距离最小的三对区域的重心作为控制点。区域匹配是通过对AMI的距离测量来实现的。区域匹配的评估是通过比较参考图像和感测图像中建立在这些三点对上的三个三角形的角度来执行的。利用这三对控制点可以计算仿射变换的参数。该算法应用于有效的DRIVE数据库。一般来说（对于这种情况，每个感测图像是通过以不同的角度、比例因子和平移因子旋转、缩放和平移参考图像来产生的），成功率和准确度分别为95%和96%。
In this study, we have introduced an accurate retinal images registration method using affine moment invariants (AMI's) which are the shape descriptors. First, some closed-boundary regions are extracted in both reference and sensed images. Then, AMI's are computed for each of those regions. The centers of gravity of three pairs of regions which have the minimum of distances are selected as the control points. The region matching is performed by the distance measurements of AMI's. The evaluation of region matching is performed by comparing the angles of three triangles which are built on these three-point pairs in reference and sensed images. The parameters of affine transform can be computed using these three pairs of control points. The proposed algorithm is applied on the valid DRIVE database. In general (for the case, each sensed image is produced by rotating, scaling, and translating the reference image with different angles, scale factors, and translation factors), the success rate and accuracy is 95 and 96 %, respectively.