计算机视觉：提取有关给定轮廓的形状的信息（例如尖的、圆形的......）
给定线条和顶点形式的形状的 2D 轮廓，如何从中提取信息？ 比如：尖的、圆的、直线。 形状与给定形状的相似度。
代码不是必需的，我更感兴趣 涉及的概念和技术名称 指导我的搜索......
提前致谢。
Given the 2D contour of a shape in the form of lines and vertices, how can I Extract Information from that?
like: Pointy, round, straight line.
Shape similarities with a given shape.
Code is not necessary, I am more interested in
concepts and the names of techniques involved to
guide my search....
Thanks in advance.
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图像矩
一种方法是计算二维轮廓所描述的形状的一阶和二阶中心矩。使用这些值可以计算物体的伸长率。
中心图像矩可以组合为Hu的七个矩，它们对于尺度、旋转和平移的变化具有不变性（即它们对于基本形状识别非常有用）。 （有关图像时刻的更多信息此处）。
周长和面积的无单位比率
另一种方法是计算周长 (p) 和内切面积 (a) 的大小。使用这两个值，可以计算出以下比率：
ratio = p^2 / (4 * pi * a)
该比率越接近 1，所描述的形状就越像圆形。
其他方法
Image moments
One approach is to calculate the first and second order central moments of the shape described by the 2D contour. Using these values the elongation of the object can be calculated.
The central image moments can be combined to the seven moments of Hu, which are invariant to change in scale, rotation and translation (ie. they are very good for basic shape recognition). (More on image moments here).
Unitless ratio of perimeter and area
An other approach is to calculate the length of the perimeter (p) and the size of the inscribed area (a). Using these two values, the following ratio can be computed:
ratio = p^2 / (4 * pi * a)
The closer this ratio is to one, the more circle like is the described shape.
Other methods
轮廓形状分类的另一种方法是基于“尺寸函数”的拓扑方法，这对于全局形状识别有用，但不适用于提取“局部”特征，例如尖/圆/直。
http://en.wikipedia.org/wiki/Size_function
基本上通过参数化线切割轮廓并根据参数计算连接组件的数量。
http://www.ingre.unimo.it/staff/landi/文章/patrec.pdf
Another method of contour shape classification is topological aproach based on the "size function" That could be useful for global shape recognition, but not for extracting "local" features like pointy/round/straight.
http://en.wikipedia.org/wiki/Size_function
Basically slicing contour by parametrized line and counting number of connected components depending on parameter.
http://www.ingre.unimo.it/staff/landi/articoli/patrec.pdf
我认为您可能正在寻找的通常称为 Blob 或连接分析，我相信最初由 SRI（斯坦福研究所）开发。图像时刻是该领域的组成部分之一。
What I think you might be looking for is often called Blob or Connectivity Analysis, which I believe was first developed at SRI (Stanford Research Institute). Image moments are one component of this area.