Description: 我用matlab写的一个corner detector, 效果比现在流行的harris，susan，CSS等效果要好。
Algorithm is derived from:
X.C. He and N.H.C. Yung, Curvature Scale Space Corner Detector with Adaptive Threshold and Dynamic Region of Support , Proceedings of the 17th International Conference on Pattern Recognition, 2:791-794, August 2004.
Improved algorithm has been included in A Corner Detector based on Global and Local Curvature Properties and submitted to Optical Engineering.
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Size: 60711 |
Author:sam he |
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Description: 使用绘制圆弧的方法，输出一个统计图表“圆饼图”和一个“折扇”。 原始数据在数组Data中，这5个数据在圆饼图中为角度不同的扇形，各自角度的计算值分别为38、91、54、125、53，放在数组drgree中。第一个数据的扇形起始角start=0，用绿色画。第二个的起始角start=38，用蓝色画。最后一个的起始角start=308，用橙色画。 折扇的画法是：在左上角坐标（130，40），长150，宽80的椭圆区域内，从22度开始逆时针地画一个15度的扇性，再画一段15度的椭圆弧；然后交替地画扇形和圆弧。-use mapping arc method, output a statistical charts, "Yuan pie" and a "folding fans." The raw data in the array Data, this data in the five round pie for the fan perspective, the perspective of their respective values were calculated 38,91,54,125,53, on the array were drgree. No. 1 fan initial data Kok start = 0, green painted. The second start of the initial angle = 38, painted blue. A final start of the initial angle = 308, with orange painting. Folding fans of paint is : in the upper left corner coordinates (130,40), 150 long, wide oval region of 80, from 22 degrees to start painting an anti-clockwise 15 degrees fan, painting section 15 of ellipse; Then turn to the fan-shaped and painted arc. Platform: |
Size: 960 |
Author:刘流 |
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Description: 使用绘制圆弧的方法，输出一个统计图表“圆饼图”和一个“折扇”。 原始数据在数组Data中，这5个数据在圆饼图中为角度不同的扇形，各自角度的计算值分别为38、91、54、125、53，放在数组drgree中。第一个数据的扇形起始角start=0，用绿色画。第二个的起始角start=38，用蓝色画。最后一个的起始角start=308，用橙色画。 折扇的画法是：在左上角坐标（130，40），长150，宽80的椭圆区域内，从22度开始逆时针地画一个15度的扇性，再画一段15度的椭圆弧；然后交替地画扇形和圆弧。-use mapping arc method, output a statistical charts, "Yuan pie" and a "folding fans." The raw data in the array Data, this data in the five round pie for the fan perspective, the perspective of their respective values were calculated 38,91,54,125,53, on the array were drgree. No. 1 fan initial data Kok start = 0, green painted. The second start of the initial angle = 38, painted blue. A final start of the initial angle = 308, with orange painting. Folding fans of paint is : in the upper left corner coordinates (130,40), 150 long, wide oval region of 80, from 22 degrees to start painting an anti-clockwise 15 degrees fan, painting section 15 of ellipse; Then turn to the fan-shaped and painted arc. Platform: |
Size: 1024 |
Author:刘流 |
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Description: 我用matlab写的一个corner detector, 效果比现在流行的harris，susan，CSS等效果要好。
Algorithm is derived from:
X.C. He and N.H.C. Yung, Curvature Scale Space Corner Detector with Adaptive Threshold and Dynamic Region of Support , Proceedings of the 17th International Conference on Pattern Recognition, 2:791-794, August 2004.
Improved algorithm has been included in A Corner Detector based on Global and Local Curvature Properties and submitted to Optical Engineering.
-err Platform: |
Size: 60416 |
Author:sam he |
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Description: 提出了一种快速准确车辆牌照的分割方法。首先利用形态学算子获取车牌的候选区域，剔除较小的和较大的区域；对保留的候选区域利用Trajkovic算法获取角点；最后对检测后的结果聚类，从而分割出包含车牌区域的子图像。-A fast and accurate method of vehicle license division. First of all, the use of morphological operators to obtain license plate candidate regions, excluding the smaller and larger areas to retain the use of the candidate region to obtain Corner Trajkovic algorithm Finally, after testing the results of clustering, which contains the license plate segmentation region sub-image. Platform: |
Size: 198656 |
Author:jiangkai |
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Description: SUSAN算子用于角点检测的基本步骤： 1） 对于感兴趣的每个象素点（一般的情况就是图像中的每个象素点）作用一圆模板； 2） 根据亮度比较函数计算圆模板中的USAN区域； 3） 根据几何阈值，计算象素点的初始响应； 4） 使用USAN重心与核中心的距离法则去除伪角点，使用USAN重心与核中心的连线上的每个点都必须在USAN区域来保证算法的一致性（即USAN区域的相连性） 5） 对每个象素点的响应，使用 （或更大）的窗口搜索局部极大值，进行非极大值抑制 -SUSAN operator for corner detection of the basic steps: 1) For each pixel of interest points (the general situation is that each image pixel points) the role of one circle template 2) calculated according to the brightness comparison function round Usan template region 3) According to the geometric threshold, calculating the pixel-point initial response 4) the use of Usan center of gravity and nuclear center removed from the law of pseudo-corner, the use of Usan center of gravity and nuclear center to connect the each point must be in the Usan region to ensure consistency algorithm (that is linked to sexual Usan region) 5) points for each pixel in response to, the use of (or greater) of the local maxima search window for non-polar large value of inhibition Platform: |
Size: 4109312 |
Author:张妙言 |
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Description: 这是用matlab写的一个corner detector, 效果比现在流行的Harris，susan，CSS等效果要好。 Matlab
确实如此，效果很好，不管是边缘还是角点
-Algorithm is derived from: X.C. He and N.H.C. Yung, Curvature Scale Space Corner Detector with Adaptive Threshold and Dynamic Region of Support , Proceedings of the 17th International Conference on Pattern Recognition, 2:791-794, August 2004. Improved algorithm has been included in A Corner Detector based on Global and Local Curvature Properties and submitted to Optical Engineering Platform: |
Size: 996352 |
Author:晓宇 |
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Description: In this paper, we propose a novel medical
registration approach based on minimal spanning tree. The
proposed approach has the following contributions. (1)
Compared with single type of feature points, we extracted
corner-like and edge-like points from image, and added a few
random points to cover the low contrast regions. (2) Instead of
fixing the multi-feature points in the whole procedure, they are
hierarchically updated at different registration stages. (3)
Based on the feature points, in addition to using pixel intensity,
we also added region based feature to include more spatial
information. The proposed method is evaluated by performing
registration experiments on BrainWeb. The experimental
results show that the proposed method achieves better
robustness while maintaining good registration accuracy,
compared to the conventional normalized mutual information
(NMI) based registration method Platform: |
Size: 253952 |
Author:Salkoum |
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Description: 1。将Canny边缘检测器应用于灰度图像，得到二值边缘图。
2。从边缘图中提取边缘轮廓，填补等高线上的空白。
三.计算每个轮廓的低曲率以保持所有真实的角，所有曲率的局部极大值被认为是初始角点。
4。使用自适应局部阈值来去除初始角点，以去除圆角。
5。角候选的角度进行评估，以消除任何虚假角落由于量化噪声和琐碎的细节。上述评价基于一个动态的支持区域，该区域根据其相邻的角候选对象进行更改。
6。轮廓线的端点被认为有附加的标准。(1. Apply the Canny edge detector to the grey level image and obtain a binary edge-map.
2. Extract the edge contours from the edge-map, fill the gaps in the contours.
3. Compute curvature at a low scale for each contour to retain all true corners.All of the curvature local maxima are considered as initial corner candidates.
4. Initial corner candidates are compared using an adaptive local threshold to remove the round corners.
5. The angles of corner candidates are evaluated to eliminate any false corners due to quantization noise and trivial details. The above evaluation is based on a dynamic region of support, which changes according to its adjacent corner candidates.
6. End points of contours are considered with an additional criterion.) Platform: |
Size: 109568 |
Author:下一秒
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Search - Region from corner