删除方形对象 [英] Removing square objects

问题描述

>

图像包括圆形，椭圆形，正方形的对象和像这样的东西。我想得到只有循环对象。我应用了一个过滤器，通过使用对象的稠度和偏心水平，但我不能删除方形对象。

I have the image includes circular, elipsoidal, square objects and somethings like these. I want to get only circual objects. I applyed a filter by using Solidity and Enccentricity levels of objets but I could not remove square objects. Square objects which have not sharp corners have nearly same Solidity and Enccentricity level with circular objects.

我的问题是，是否有任何其他参数或方法来检测方形对象？ / p>

My question is that is there any other parameter or way to detect square objects?

推荐答案

您可以使用以下公式比较面具的面积与其周长：

You can compare the area of the mask to its perimeter using the following formula

ratio = 4 * pi * Area / ( Perimeter^2 )

对于圆，这个比率应该非常接近一个，对于其他形状，它应该显着降低。

参见

For circles this ration should be very close to one, for other shapes it should be significantly lower.
See this tutorial for an example.

这个公式背后的理由：圆圈在周长上是最佳的 - 给定周长的面积比 - 最大面积。给定周长，您可以使用估计的 R 估计 Perimeter = 2 * pi * R 可以使用 eqArea = pi * R ^ 2 计算等效圆面积。现在你只需要检查形状的实际面积和计算的等效面积之间的比率。

The rationale behind this formula: circles are optimal in their perimeter-area ratio - max area for given perimeter. Given Perimeter, you can estimate radius of equivalent circle by Perimeter = 2*pi*R, using this estimated R you can compute the "equivalent circle area" using eqArea = pi*R^2. Now you only need to check the ratio between the actual area of the shape and the "equivalent area" computed.

注意：因为 code>和周界中的对象基于像素级离散估计，这些估计可能是相当粗糙的，特别是对于小形状。如果您注意到量化/离散错误，请考虑使用更高分辨率的掩码。

Note: since Area and Perimeter of objects in mask are estimated based on the pixel-level discretization these estimates may be quite crude especially for small shapes. Consider working with higher resolution masks if you notice quantization/discretization errors.

这篇关于删除方形对象的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！