Question

我正在使用the page中的代码。它适用于我的大多数图像。但它在附加图像上失败 - 代码无法识别仪表的外部刻度盘/边界（在我的原始图像中，没有内部白色圆圈）

知道可能出现什么问题吗？

Answer 1

这就是你所追求的......

如果是这样，那就是调整一些参数的问题。特别是，最小和最大圆半径和circle_distance（检测到的圆之间的最小距离）。

要点here。

<强>更新
如果你想将最小半径与图像尺寸联系起来，你可以这样做：

float minRadius = MIN(img.size().width, img.size().height) * 0.5;

并将其提供给houghCircles函数。

我实际使用的参数（按照要点）：

 HoughCircles(     img
                 , circles
                 , CV_HOUGH_GRADIENT //method – Detection method to use. 
                 // Currently,  the only implemented method is 
                 // CV_HOUGH_GRADIENT , which is  basically 21HT , 
                 // described in [Yuen90].
                 , 1 //p – Inverse ratio of the accumulator resolution to the 
                 // image resolution. For example, if dp=1 , the accumulator has 
                 // the same resolution as the input image. If dp=2 , 
                 // the accumulator has half as big width and height.
                 , 60  //minDist – Minimum distance between the centers of the 
                 // detected circles. If the parameter is too small, multiple 
                 // neighbor circles may be falsely detected in addition to a 
                 // true one. If it is too large, some circles may be missed.
                 , 100 //cannyThreshold – The higher threshold of the two 
                 // passed  to the gpu::Canny() edge detector 
                 // (the lower one is twice smaller).
                 , 30 //votesThreshold – The accumulator threshold for the circle 
                 // centers at the detection stage. The smaller it is, the more 
                 // false circles may be detected.
                 , 250 //minRadius – Minimum circle radius.
                 , 300 //maxRadius – Maximum circle radius.
                 );

评论从openCV documentation解除。

LINUX opencv hough变换圈

1 个答案: