Description: hough变换，用于直线和圆，椭圆的检测，很实用-hough transform for line and circle, ellipse detection, it is practical Platform: |
Size: 12288 |
Author:郑海珍 |
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Description: 介绍了一种椭圆检测的方法，该方法，基于霍夫变换，并根据椭圆几何特征可以快速准确的提取出椭圆中心。本论文为收费文献，现共享，希望对研究计算机视觉以及近景摄影测量的朋友，有所帮助。-Introduce a kind of ellipse detection method, based on the Hough transform, and in accordance with the characteristics of elliptical geometry can be extracted quickly and accurately center oval. This thesis documents for a fee, are sharing the hope that the study of computer vision, as well as close-range photogrammetry friends, be helpful. Platform: |
Size: 308224 |
Author:刘镖峰 |
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Description: 针对多椭圆检测问题提出了一种快速随机检测算法。该算法利用在图像中随机采样到的一个边缘点和
局部搜索到的两个边缘点以及这三个点的邻域信息确定候选椭圆,再将候选椭圆变换为对应圆,通过确认真圆来确
认真椭圆。在确定候选椭圆时,最大限度地减少随机采样点数‰ 剔除更多的非椭圆点,降低了无效采样,减少了无效
计算。数值实验结果表明:该算法具有良好的鲁棒性,其检测速度比同类算法快-Ellipse detection problem for many a fast random detection algorithm. The algorithm uses random sampling in the image of an edge point and the local search to the two edge points, as well as the three-point neighborhood information to determine the candidate ellipse, and then transformed into the corresponding elliptical candidate won, through the identification of real yen to confirm really elliptical. In determining when a candidate ellipse, to minimize random sampling points ‰ remove more non-oval points, reducing invalid sampling, to reduce the calculation invalid. Numerical experimental results show that: the algorithm has good robustness, and its detection faster than similar algorithms quickly Platform: |
Size: 526336 |
Author:刘镖峰 |
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Description: 利用Matlab编写的基于hough变换的椭圆检测程序，已经运行过的，附图-Written in Matlab, hough transform based ellipse detection procedure has been run off, with photos Platform: |
Size: 3072 |
Author:guixuzhen |
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Description: Edge detection result should be enhanced using linear method like Median filter to
remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the
centre of the pupil by counting the number of black pixels (zero value) of each column and
row. Then get each row and column that has the maximum number of these black pixels.
Then determine the center by simple calculation according to the image coordinate to set it
correct on the image, consequently we can determine the radius of the pupil. Thus we can find
the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to
locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms
of circle and ellipse. Platform: |
Size: 1024 |
Author:boss |
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Search - ellipse detection in matlab