OpenCV寻找复杂背景下物体的轮廓
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一、问题提出
这是一个来自OPenCV问答社区 - "answerOpenCV"问题，整编如下： （http://answers.opencv.org/question/200422/opencv-c-filling-holes/） title：OpenCV / C++ - Filling holes content: Hello there, For a personnel projet, I'm trying to detect object and there shadow. These are the result I have for now: Original:
Object: Shadow: The external contours of the object are quite good, but as you can see, my object is not full. Same for the shadow. I would like to get full contours, filled, for the object and its shadow, and I don't know how to get better than this (I juste use "dilate" for the moment). Does someone knows a way to obtain a better result please? Regards.
二、问题分析
从原始图片上来看，这张图片的拍摄的背景比较复杂，此外光照也存在偏光现象；而提问者虽然提出的是“将缝隙合并”的要求，实际上他还是想得到目标物体的准确轮廓。
三、问题解决
基于现有经验，和OpenCV，GOCVhelper等工具，能够很快得出以下结果 h通道：
去光差：
阈值:
标注：
四、算法关键
这套算法首先解决了这个问题，而且我认为也是稳健鲁棒的。其中，算法中除了经典的“hsv分解->ostu阈值->最大轮廓标注”外，最为关键的算法为顶帽去光差。这个算法来自于冈萨雷斯《数字图像处理教程》形态学篇章，完全按照书本建议实现，体现良好作用。
//answerOpenCV OpenCV / C++ - Filling holes
#include "stdafx.h"
#include <iostream>
#include <vector>
using namespace cv;
using namespace std;
//find the biggest contour
vector<Point> FindBigestContour(Mat src){
int imax = 0;
int imaxcontour = -1;
std::vector<std::vector<Point> >contours;
findContours(src,contours,CV_RETR_LIST,CV_CHAIN_APPROX_SIMPLE);
for (int i=0;i<contours.size();i++){
int itmp = contourArea(contours[i]);
if (imaxcontour < itmp ){
imax = i;
imaxcontour = itmp;
}
}
return contours[imax];
}
//remove Light difference by using top hat
Mat moveLightDiff(Mat src,int radius){
Mat dst;
Mat srcclone = src.clone();
Mat mask = Mat::zeros(radius*2,radius*2,CV_8U);
circle(mask,Point(radius,radius),radius,Scalar(255),-1);
//top hat
erode(srcclone,srcclone,mask);
dilate(srcclone,srcclone,mask);
dst = src - srcclone;
return dst;
}
int main( void )
{
Mat src = imread("e:/sandbox/question.png");
Mat src_hsv;
Mat bin;
Mat src_h;
cvtColor(src,src_hsv,COLOR_BGR2HSV);
vector<Mat> rgb_planes;
split(src_hsv, rgb_planes );
src_h = rgb_planes[0]; // h channel is useful
src_h = moveLightDiff(src_h,40);
threshold(src_h,bin,100,255,THRESH_OTSU);
//find and draw the biggest contour
vector<Point> bigestcontrour = FindBigestContour(bin);
vector<vector<Point> > controus;
controus.push_back(bigestcontrour);
cv::drawContours(src,controus,0,Scalar(0,0,255),3);
waitKey();
return 0;
}五、经验小结
解决这个问题我只用了10分钟的时间，写博客10分钟。能够快速解决问题并书写出来的关键为： 1、积累维护的代码库: GOCVHelper(https://github.com/jsxyhelu/GOCvHelper） 2、不断阅读思考实践的习惯； 禾路 【OpenCV研习社】知识星球嘉宾 目前方向：图像拼接融合、图像识别 联系方式：jsxyhelu@foxmail.com
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