问题描述
我们一直在学习像 Sobel 和 Roberts 的卷积矩阵这样的方法来检测图像中的边缘，扩展到 Canny 方法来清除它们.但是现在，我们正在学习线"检测，而不是边缘"检测 - 使用霍夫变换等方法.
We have been learning about methods like Sobel and Roberts' convolution matrices to detect edges within images, extending to the Canny method to clear them up. But now, we are learning about 'Line' detection, as opposed to 'Edge' detection - with methods like Hough Transform.
问题是 - 我什至不知道如何概念化线"和边"之间的区别.有人可以在不使用复杂的数学方程等的情况下向我解释这种差异吗?
Problem is - I've no idea how to even conceptualize the difference between a 'Line' and an 'Edge'. Can someone explain this difference to me without the use of complex mathematical equations etc?
推荐答案
边缘是从一个阶段/对象/事物到另一个阶段的过渡.一方面你有一种颜色，另一方面你有另一种颜色.或者一侧有前景，另一侧有背景.
An edge is a transition from one phase/object/thing to another. On one side you have one color, on the other side you have another color. Or on one side you have foreground, and on the other side you have background.
线是一维结构.它在两侧具有相同的相位/物体/事物.一方面你有背景，另一方面你也有背景.
A line is a 1D structure. It has the same phase/object/thing on either side. On one side you have background, on the other side you have background also.
梯度幅度过滤器将边缘变成一条线.
A gradient magnitude filter turns an edge into a line.
一条边有一个方向(法线)，一条线有一个方向(如果你把它旋转 180 度，它看起来是一样的).
An edge has a direction (the normal), a line has an orientation (if you rotate it by 180 degrees, it looks the same).
你可以把一条线想象成两条非常靠近的相对边.
You can think of a line as being two opposite edges very close together.
线条和边缘都是图像的局部属性.图像中任何足够小的部分都将显示为边缘或线条.
Lines and edges are both local properties of an image. Any sufficiently small portion of an image will appear as either an edge or a line.
它们都是局部笔直的，因为在足够小的区域内考虑弯曲的东西会显得笔直.
They are both locally straight, since something curved, considered in a sufficiently small region, will appear straight.
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