三维霍夫空间
我正在搜索图像中圆的半径和中心坐标。已经尝试过二维霍夫变换。但我的圆半径也是未知的。我仍然是计算机视觉的初学者,因此需要引导线和帮助来实现三维霍夫空间。
Im searching for radius and the center coordinates of circle in a image. have already tried 2D Hough transform. but my circle radius is also a unknown. Im still a beginner to Computer vision so need guild lines and help for implementing three dimensional hough space.
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您可以像二维霍夫空间一样实现它,但需要一个附加参数。伪代码如下所示:
You implement it just like 2D Hough space, but with an additional parameter. Pseudo code would look like this:
Thiton 为您提供了将问题形式化的正确方法。但随后,您将遇到霍夫变换固有的其他问题:
如何可视化参数空间?您可以使用像 VTK 这样的库来实现一些东西,但是数据的 3D 可视化始终是一个困难的话题。可视化对于调试检测算法非常重要,并且是 2D 霍夫变换的好处之一
局部最大值检测并非微不足道。新的维度将意味着你的参数空间将更加稀疏。您将在该区域进行更多调整
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如果你正在寻找一个圆检测算法,你可能有比霍夫变换更好的选择(谷歌“使用梯度对向量的快速圆检测”对我来说看起来不错)
Thiton gives you the correct approach to formalize the problem. But then, you will run in other problems inherent to the hough transform:
how do you visualize the parameter space? You may implement something with a library like VTK, but 3D visualization of data is always a difficult topic. The visualization is important for debugging your detection algorithm and is one of the nice thing with 2D hough transform
the local maximum detection is non trivial. The new dimension will mean that your parameter space will be more sparse. You will have more tuning to do in this area
If you are looking for a circle detection algorithm, you may have better options than the hough transform (google "Fast Circle Detection Using Gradient Pair Vectors" looks good to me)