opencv视频分析与对象追踪之基于颜色

适用场景

根据画面中对象的颜色进行识别追踪，此种方法有一定局限性，首先目标颜色一定要与其他背景有着非常明显的区分，光照条件不经常变化不会导致对象颜色的突变。

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处理思路

• 利用颜色范围过滤
• 标注与测量

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操作步骤

• inRange过滤
• 形态学操作提取
• 轮廓查找
• 外接矩形获取
• 位置标定

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代码

#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>

using namespace std;
using namespace cv;

int main(void)
{
     Mat frame,mask,dst;
    VideoCapture cap;

    namedWindow("inputvideo",0);
    resizeWindow("inputvideo",272,480);

    namedWindow("track mask",0);
    resizeWindow("track mask",272,480);

    namedWindow("dst",0);
    resizeWindow("dst",272,480);

    if(!cap.open("/work/opencv_video/color_check.mp4"))
    {
        cout << "video is err" << endl;
        return -1;
    }

    //开操作 掩膜
    Mat kernel = getStructuringElement(MORPH_RECT,Size(3,3));
    Rect rect;
    while(true)
    {
        cap>>frame;
        if(frame.empty())
        {
            break;
        }
        imshow("inputvideo",frame);
        dst = frame.clone();
        cvtColor(frame,frame,COLOR_BGR2HSV);

        inRange(frame,Scalar(35,43,46),Scalar(77,255,255),mask);

        //开操作 消除噪点
        morphologyEx(mask,mask,MORPH_OPEN,kernel);
        imshow("track mask",mask);

        vector<vector<Point>> contours;
        findContours(mask,contours,RETR_TREE,CHAIN_APPROX_SIMPLE);
        for(size_t i=0;i<contours.size();i++)
        {
            rect = boundingRect(contours[i]);
            if(rect.width >10 && rect.height >10 )
            {
                rectangle(dst,rect,Scalar(0xF7,0x09,0xF7),3);
            }
        }
        imshow("dst",dst);


        if(waitKey(100)>0)
            break;
    }
    cap.release();
    destroyAllWindows();
    return 0;
}

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效果

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