图像分割教案.pptVIP

图像分割 极小点 面向区域的分割 基本概念 4)单一性：每个区域内的灰度级相等， P（Ri）= TRUE，i = 1,2,…,n 5)互斥性：任两个区域的灰度级不等， P（Ri∪Rj）= FALSE，i≠j 面向区域的分割 通过像素集合的区域增长(region grow) 算法实现： 面向区域的分割 像素集合的区域增长 算法实现： 1）根据图像的不同应用选择一个或一组种子，它或者是最亮或最暗的点，或者是位于点簇中心的点 2）选择一个描述符（条件） 3）从该种子开始向外扩张，首先把种子像素加入结果集合，然后不断将与集合中各个像素连通、且满足描述符的像素加入集合 4）上一过程进行到不再有满足条件的新结点加入集合为止 区域分裂与合并 算法实现： 区域分裂与合并 算法实现：实际应用中还可作以下修改： P(Ri)的定义为： 1）区域内多于80%的像素满足不等式 |zj-mi|=2σi， 其中：zj是区域Ri中第j个点的灰度级， mi是该区域的平均灰度级， σi是区域的灰度级的标准方差。 2）当P(Ri)=TRUE时，将区域内所有像素的灰度级置为mi。 边缘检测 Lets define an edge to be a discontinuity in image intensity function. Edge Models Step Edge Ramp Edge Roof Edge Spike Edge Canny Edge detector(p16) 边缘跟踪与连接 An edge is not a line... Finding lines in an image Option 1: Search for the line at every possible position/orientation What is the cost of this operation? Option 2: Use a voting scheme: Hough transform Finding lines in an image Connection between image (x,y) and Hough (m,b) spaces A line in the image corresponds to a point in Hough space To go from image space to Hough space: given a set of points (x,y), find all (m,b) such that y = mx + b Hough transform algorithm Typically use a different parameterization d is the perpendicular distance from the line to the origin ? is the angle this perpendicular makes with the x axis Why? Hough transform algorithm Typically use a different parameterization d is the perpendicular distance from the line to the origin ? is the angle this perpendicular makes with the x axis Why? Basic Hough transform algorithm Initialize H[d, ?]=0 for each edge point I[x,y] in the image for ? = 0 to 180 H[d, ?] += 1 Find the value(s) of (d, ?) where H[d, ?] is maximum The detected line in the image is given by What’s the running time (measured in # votes)? Hough demos Hough Transform for Curves The H.T. can be generalized to detect any curve that can be expressed in parametric form: Y = f(x, a1,a2,…ap) a1, a2, … ap are the parameters The parameter space is p-dimensional The accumul