bianyuangaijinquanjuyuzhi.zip_基于边缘改进的阈值处理_边缘 分割_阈值 分割_阈值分割

%使用边缘改进全局阈值处理 clc; clear all; close all; sourcPic = imread('19.jpg'); I =rgb2gray(sourcPic); %T=graythresh(I); %平滑 w=fspecial('average',20); I=imfilter(I,w,'replicate'); f=im2double(I); %sx=fspecial('prewitt');%用于边缘增强 sx=fspecial('sobel'); %fspecial函数用于建立预定义的滤波算子 sy=sx';%‘代表矩阵转置 gx=imfilter(f,sx,'replicate');%对任意类型数组或多维图像进行滤波 ，'replicate'图像通过外边界值来拓展 gy=imfilter(f,sy,'replicate'); grad=sqrt(gx.*gx+gy.*gy); grad=grad/max(grad(:)); h=imhist(grad); Q=percentile2i(h,0.95);%计算给定百分比的灰度值 markerImage=grad>Q; %细化 markerImage=bwmorph(markerImage,'thin',Inf); %腐蚀 markerImage=bwareaopen(markerImage,1000);%；将小于2000像素的单元去掉 %markerImage = bwmorph(markerImage,'open',Inf); %开运算 %markerImage = bwmorph(markerImage,'bridge',Inf);%连接断开的像素。也就是将0值像素置1如果他有两个非零的不相连（8邻域）的像素 %markerImage = bwmorph(markerImage,'fill',Inf);%填充中间的洞 %markerImage = bwmorph(markerImage,'majority',Inf); markerImage = bwmorph(markerImage, 'spur',Inf);%去毛刺 figure,imshow(markerImage); fp=f.*markerImage; figure,imshow(fp); %hp=imhist(fp); %hp(1)=0; %bar(hp,0); %T=otsuthresh(hp);%给定直方图最佳阈值 %g=im2bw(f,T); %figure,imshow(g);