Python图像-从图像骨架中找到最大的分支 [英] Python Image - Finding largest branch from image skeleton

问题描述

我有以下形状的骨架化图像:

我想从骨架中提取最大分支":

我知道也许我需要提取接合点并从该点(?)上划分线，但是我不知道如何做到这一点.

是否可以使用Python Scikit Image或OpenCV做到这一点?

解决方案

我相信您可以使用OpenCV执行以下操作:

1. 使用

   2. 在所有角落添加黑色像素

   3. 使用 findContours 获取图片中的所有分支.然后使用 arcLength 并获得最长的时间.

   I have a skeletonized image in the following shape:

   And I want to extract the "largest branch" from the skeleton:

   I know that maybe I need to extract the junction point and divide de lines from that point(?), but I have no clue how to do that.

   Is there any way to do that with Python Scikit Image or OpenCV?

   解决方案

   I believe you can use OpenCV to do the following:

   1. Use HarrisCorner to detect all corners in the image. This will get you the shown three green points (I drew a whole circle to highlight the location).

   2. Add a black pixel at all corners

   3. Get all branches in the picture using findContours. Then check the length of each contour using arcLength and get the longest.

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