如何在OpenCV中平滑曲线(轮廓)? [英] How do i smooth the curves(contours) in OpenCV?

问题描述

我正在处理黑白图像，就像该链接中的第一个图像一样: http://imageshack.us/g/33/firstwm.png/ 它具有很多噪声"，因此我在其上应用了中值滤镜以使其平滑，从而获得了第二张图片.

I am working on a black&white image just like the first one from the link : http://imageshack.us/g/33/firstwm.png/ It has a lot of "noise" so I applied a Median filter over it to smooth it, thus getting the second picture.

cvSmooth(TempImage, TempImage, CV_MEDIAN, 5, 0);

在此之后，我得到了轮廓并将其绘制在另一个图像上，如链接中的第3张图片. 我的问题是轮廓仍然有点像素化(前卫).有没有一种方法可以使黑白图像更加平滑，从而获得更好的轮廓?或对轮廓进行一些处理. 我还尝试了使用不同内核的Dilate和Erode，但问题仍然相同. 谢谢您的帮助.

After this i get the contours and draw them on another image like the 3rd picture from the link. My problem is that the contours are still a little pixelated(edgy). Is there a way to smooth the B&W image even more so to obtain better contours? Or maybe do something with the contours. I have also tried Dilate and Erode with different kernels but the problem remains the same. Thank you for anything that helps.

也尝试过:

cvSmooth(TempImage, TempImage, CV_GAUSSIAN, 9, 9, 3);
cvThreshold(TempImage, TempImage, 127, 255, CV_THRESH_BINARY);

与中值过滤器的结果相同，但是，仍然保留了一些像素化的轮廓.

Same results as median filter, ok, but still leaves some pixelated contours.

推荐答案

如果这是您想要的平滑结果，则可以通过进行高斯模糊，然后进行阈值处理来获得. IE.将cvSmooth与CV_GAUSSIAN用作参数.后跟cvThreshold.

If this is the smoothing result you're after, it can be obtained by doing a Gaussian blur, followed by a thresholding. I.e. using cvSmooth with CV_GAUSSIAN as the paramater. Followed by a cvThreshold.

如果您想要比阈值更平滑的过渡(例如此)，则可以得到调整级别(重新映射颜色范围，以便保留一些边缘过渡).

If you want a smoother transition than thresholding (like this), you can get that with adjusting levels (remapping the color range so that you preserve some of the edge transition).

更新要说明如何获得阈值上的平滑(抗锯齿)边缘，请考虑阈值的作用.它基本上处理图像中的每个像素，一次处理一个.如果像素值低于阈值，则将其设置为黑色(0)，否则将其设置为白色(255).

update To explain how to get the smooth (anti-aliased) edge on the thresholding, consider what the thresholding does. It basically processes each pixel in the image, one at a time. If the pixel value is lower than the threshold, it is set to black (0), if not it is set to white (255).

因此，阈值运算符非常简单，但是，可以使用任何其他常规映射函数.基本上，它是一个函数f(i)，其中i是强度像素值(范围为0-255)，而f(i)是映射值.对于阈值，此功能很简单

The threshold operator is thus very simple, however, any other general mapping function can be used. Basically it's a function f(i), where i is the intensity pixel value (ranged 0-255) and f(i) is the mapped value. For threshold this function is simple

 f(i) = {   0, for i  < threshold
          255, for i >= threshold

您拥有的是平滑图像(通过cvSmooth使用高斯内核，如果可以的话，它可以为您提供最平滑"的平滑).因此，您在边缘上具有从0到255范围内的值的软过渡.您想要做的是使此过渡小得多，以便获得良好的边缘.如果对它进行弹道射击，则直接从0到255，这与您已经完成的二进制阈值相同.

What you have is a smoothed image (by cvSmooth using a Gaussian kernel, which gives you the "smoothest" smoothing, if that makes sense). Thus you have a soft transition of values on the edges, ranging from 0 to 255. What you want to do is make this transition much smaller, so that you get a good edge. If you go ballistic on it, you go directly from 0 to 255, which is the same as the binary thresholding you've already done.

现在，考虑一个将4个强度值(127 + -4)范围映射到0-255整个范围的函数.即

Now, consider a function that maps, maybe a range of 4 intensity values (127 +- 4) to the full range of 0-255. I.e.

         f(i) = {   0,  for i  < 123
                  255,  for i >= 131
       linear mapping,  for 123 <= i < 131

您将获得所需的输出.我将快速浏览一下，看看它是否已经在openCV中实现.不过，自己编写代码也不应该太难.

And you get the desired output. I'll take a quick look and see if it is implemented in openCV already. Shouldn't be too hard to code it yourself though.

更新2 轮廓版本将如下所示:

update 2 The contour version would be something like this:

              f(i) = { 255,  for        i < 122
   linear mapping (255->0),  for 122 <= i < 126
                         0,  for 126 <= i < 127
   linear mapping (0->255),  for 127 <= i < 131
                       255,  for 131 <= i

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