Segmentation obtained by thresholding the UCM at certain level_from contours to regions: an empirical evaluation-优快云博客

转自：https://blog.youkuaiyun.com/skye1221/article/details/77511797

这里写图片描述

这篇主要讲如何获得最右边的结果，论文可以参考：
From Contours to Regions: An Empirical Evaluation
Contour Detection and Hierachical Image Segmentation

根据上图，我们可以得到一般的思路，给定原图和其对应的UCM以及某个参数因子，就可以得到我们想要的结果。大致步骤如下：
1、读取某一原图及其对应的UCM
2、设定thresholding
3、根据thresholding，得到某一level的UCM map
4、对该UCM map的所有regions设定label
5、构建一个三通道的RGB矩阵，每个通道都是thresholding对应level的UCM map
6、找到所有UCM map 的label在原图对应的二维坐标
7、在原图基础上，求regions的label对应坐标位置三个通道的像素值，然后求average
8、对RGB对应的三个通道的每个regions赋值相应的average

代码如下：

load('data/101087_ucm2.mat','ucm2');
image=imread('data/101087.jpg');
%convert ucm to the size of the original image
ucm = ucm2(3:2:end, 3:2:end);

%get the boundaries of segmentation at scale k in range [0 1]
k = 0.4;
bdry = (ucm >= k);

%get superpixels at scale k without boundaries:
labels2 = bwlabel(ucm2 <= k);
labels = labels2(2:2:end, 2:2:end);

% figure;imshow('data/101087.jpg');
% figure;imshow(ucm);
% figure;imshow(bdry);
% change format
temp=mat2gray(bdry);
temp=uint8(temp*255);
%set a three channels matrix to save result,all the channel are
%identical,etc,temp. The three channel,as we all know, reprents RGB
RGB(:,:,1)=temp;
RGB(:,:,2)=temp;
RGB(:,:,3)=temp;
% the number of different label values in labels matrix
label=unique(labels);
for i=1:length(label)
    [x,y]=find(labels==i); % find the location where labels equal i
    [m,n]=size([x,y]); %m is the numberi of piexl node of the region
    sum=zeros(3,1); % make a 3x1 matrix to save the sum value
    for j=1:m  % calculate the sum
        sum(1,1)=sum(1,1)+double(image(x(j),y(j),1));
        sum(2,1)=sum(2,1)+double(image(x(j),y(j),2));
        sum(3,1)=sum(3,1)+double(image(x(j),y(j),3));
    end
    %calculate the average
    average1=round(sum(1,1)/m);
    average2=round(sum(2,1)/m);
    average3=round(sum(3,1)/m);
    for k=1:m
        % set each channel 
        RGB(x(k),y(k),1)=uint8(average1);
        RGB(x(k),y(k),2)=uint8(average2);
        RGB(x(k),y(k),3)=uint8(average3);
    end
end
%if you want show the contour,you should need the following code
[x2,y2]=find(temp==255);
[m2,n2]=size([x2,y2]);
for i=1:m2
    %set contour for each channel
    RGB(x2(i),y2(i),1)=255;
    RGB(x2(i),y2(i),2)=255;
    RGB(x2(i),y2(i),3)=255;
end