我目前正在撰写学士学位论文以认识＆amp;使用计算机视觉方法在母鸡巢中计数鸡蛋。鸡蛋可以（部分）用母鸡阻塞一段时间，并且可以在不同的旋转中放置。我目前的想法是使用椭圆形的霍夫变换和使用YOLO的AI解决方案 - 用于跟踪，我目前正在研究:)
但是，通过skimage's tutorial about
- 什么是累加器阈值阈值的确切是什么？
- 后轴上的准确性和垃圾箱的大小是多少？
- 所有这些参数如何一起工作以找到椭圆以及min_size＆amp; max_size
（min_size是最小的主要轴长＆amp; max_ize是最大的次要轴长）
- 不是主要的＆amp;次要轴可以改变吗？
对于转换，我目前正在使用灰度 - ＆gt;高斯模糊 - ＆gt; Canny检测。
目前的预处理结果看起来像这样：
图像
预处理 - 的确 - 一个椭圆。我不确定OpenCV的Fitellipse（）是否最终会帮助我检测到椭圆，尤其是当母鸡部分遮住并具有不同的鸡蛋旋转时。
此外，如何找出Hough_transform（）的单个参数？
PS：如果有人除了AI外有更好的想法进行测试，我很乐意尝试更多的东西:)
I am currently working on a Bachelor Thesis to recognize & count eggs in a hen nest using Computer Vision methods. The eggs can be (partially) occluded by hens for a while and can be positioned in different rotations. My current ideas are using an Elliptic Hough Transform and an AI solution using YOLO - For tracking, I am currently researching :)
However, reading through skimage's tutorial about Hough_Ellipse() and trying to find resources, I am currently at a dead end which results in the following questions:
- What is an accumulator threshold value exactly?
- What is the accuracy and bin size on the minor axis?
- How do all these parameters work together to find ellipses along with min_size & max_size
(min_size is minimal major axis length & max_size is maximal minor axis length)
- Isn't it that the major & minor axis can change?
For the transform, I currently am using Grayscaling -> Gaussian Blurring -> Canny Detection.
The result of the preprocessing looks like this at the moment:
Preprocessed Image
The preprocessing shows that there is - indeed - an ellipse. I am unsure whether FitEllipse() from OpenCV will end up helping me detecting Ellipses, especially when partially occluded by hens and having different possible rotations of an egg.
Furthermore, how do I figure out the individual parameters for Hough_Transform()?
PS: If anyone has better ideas aside from AI to test out, I'd be happy to try out more things :)
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