数组的加权质心 [英] Weighted Centroid of an Array

问题描述

所以我有一个二维数组代表一个坐标平面，一个图像。在该图像上，我正在寻找红色像素，并根据我的相机找到的所有红色像素找到（希望）红色LED目标的位置。目前，我只是将十字准线拍到所有红色像素的质心上：

  //伪代码
 
 for（cycle_through_pixels）
 {
 if（is_red（pixel [x] [y]））
 {
 vals ++; //红色像素总数
 cx + = x; //求x的
 cy + = y; //求y的
} 
} 
 cx / = vals; //除以总计得到平均值x 
 cy / = vals; //除以总计得到平均值y 
 
 draw_crosshairs_at（pixel [cx] [cy]）; //找到了质心
  

这种方法的问题在于，这种算法自然会使质心更接近最大的斑点（红色像素最多的区域），当有一些红色由于眩光或其他轻微干扰而闪烁时，我仍然看到我的十字准线跳离目标。

我的问题是：

如何更改此模式以寻找更多加权质心？简而言之，我想让较大的红色斑点比较小的斑点更重要，甚至可能完全忽略远处的小斑点。

解决方案

您可以在图像中找到连接组件，并且只包含这些组件在您的质心计算中总大小超过某个阈值。

So I have a 2-dimensional array representing a coordinate plane, an image. On that image, I am looking for "red" pixels and finding (hopefully) the location of a red LED target based on all of the red pixels found by my camera. Currently, I'm simply slapping my crosshairs onto the centroid of all of the red pixels:

// pseudo-code

for(cycle_through_pixels)
{
   if( is_red(pixel[x][y]) )
   {
      vals++; // total number of red pixels
      cx+=x;  // sum the x's
      cy+=y;  // sum the y's
   }
}
cx/=vals; // divide by total to get average x
cy/=vals; // divide by total to get average y

draw_crosshairs_at(pixel[cx][cy]); // found the centroid

The problem with this method is that while this algorithm naturally places the centroid closer to the largest blob (the area with the most red pixels), I am still seeing my crosshairs jump off the target when a bit of red flickers off to the side due to glare or other minor interferences.

My question is this:

How do I change this pattern to look for a more weighted centroid? Put simply, I want to make the larger blobs of red much more important than the smaller ones, possibly even ignoring far-out small blobs altogether.

解决方案

You could find the connected components in the image and only include those components that have a total size above a certain threshold in your centroid calcuation.

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