opencv 07 用Hausdorff距离做形状匹配(shape_example) vs2015

01 资源

OpenCV自带的行人检测demo，opencv\samples\cpp\shape_example.cpp。shape_example.cpp可以图形形状相似对比。通过判断Hausdorff距离的结果做出最匹配判断，Hausdorff距离越小，匹配度越高。
OpenCV提供20张形状图片，在路径opencv\samples\data\shape_sample中。
opencv\samples\data\shape_sample

02 编译shape_example

参考opencv01 相对完整的编译opencv3.3.0 win版本，编译opencv3.3.0 vs2015版本。
为修改参数方便，稍微修改下代码，添加path参数：

    //string path = "../data/shape_sample/";
    string path;
    cv::CommandLineParser parser(argc, argv, "{help h||}{@input|1|}{path|../data/shape_sample/|}");
    if (parser.has("help"))
    {
        help();
        return 0;
    }
    int indexQuery = parser.get<int>("@input");
    if (!parser.check())
    {
        parser.printErrors();
        help();
        return 1;
    }
    path = parser.get<string>("path");
    if (!parser.check())
    {
        parser.printErrors();
        help();
        return 2;
    }

生成文件：D:\git\opencv\build\v3.3.0\x64\bin\Debug\cpp-example-shape_example.exe

03 shape_example项目配置

设置shape_example项目为启动项。

# -@input=5，这个@input默认是1，可以选择1-20间的任何一个图片
配置属性==>调试==>命令参数=-@input=5 -path=../../../../../samples/data/shape_sample/
配置属性==>调试==>工作目录=$(OutDir)

04 运行结果

5.png和6.png的距离最小：0.0710131。

name: ../../../../../samples/data/shape_sample/1.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/1.png is: 4.05005
name: ../../../../../samples/data/shape_sample/2.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/2.png is: 22.7777
name: ../../../../../samples/data/shape_sample/3.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/3.png is: 8533.25
name: ../../../../../samples/data/shape_sample/4.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/4.png is: 10817.4
name: ../../../../../samples/data/shape_sample/6.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/6.png is: 0.0710131
name: ../../../../../samples/data/shape_sample/7.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/7.png is: 50.1265
name: ../../../../../samples/data/shape_sample/8.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/8.png is: 50.223
name: ../../../../../samples/data/shape_sample/9.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/9.png is: 15.7305
name: ../../../../../samples/data/shape_sample/10.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/10.png is: 15.0504
name: ../../../../../samples/data/shape_sample/11.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/11.png is: 8.31791
name: ../../../../../samples/data/shape_sample/12.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/12.png is: 5.07157
name: ../../../../../samples/data/shape_sample/13.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/13.png is: 6004.73
name: ../../../../../samples/data/shape_sample/14.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/14.png is: 3644.86
name: ../../../../../samples/data/shape_sample/15.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/15.png is: 1.40525
name: ../../../../../samples/data/shape_sample/16.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/16.png is: 3.90065
name: ../../../../../samples/data/shape_sample/17.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/17.png is: 10044.1
name: ../../../../../samples/data/shape_sample/18.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/18.png is: 2120.9
name: ../../../../../samples/data/shape_sample/19.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/19.png is: 8802.19
name: ../../../../../samples/data/shape_sample/20.png
 distance between ../../../../../samples/data/shape_sample/5.png and ../../../../../samples/data/shape_sample/20.png is: 2448.39

05 shape_example.cpp

/*
 * shape_context.cpp -- Shape context demo for shape matching
 */

#include "opencv2/shape.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include 
#include 
#include 

using namespace std;
using namespace cv;

static void help()
{
    printf("\n"
            "This program demonstrates a method for shape comparisson based on Shape Context\n"
            "You should run the program providing a number between 1 and 20 for selecting an image in the folder ../data/shape_sample.\n"
            "Call\n"
            "./shape_example [number between 1 and 20, 1 default]\n\n");
}

static vector simpleContour( const Mat& currentQuery, int n=300 )
{
    vector<vector > _contoursQuery;
    vector  contoursQuery;
    findContours(currentQuery, _contoursQuery, RETR_LIST, CHAIN_APPROX_NONE);
    for (size_t border=0; border<_contoursQuery.size(); border++)
    {
        for (size_t p=0; p<_contoursQuery[border].size(); p++)
        {
            contoursQuery.push_back( _contoursQuery[border][p] );
        }
    }

    // In case actual number of points is less than n
    int dummy=0;
    for (int add=(int)contoursQuery.size()-1; add//adding dummy values
    }

    // Uniformly sampling
    random_shuffle(contoursQuery.begin(), contoursQuery.end());
    vector cont;
    for (int i=0; ireturn cont;
}

int main(int argc, char** argv)
{
    //string path = "../data/shape_sample/";
    string path;
    cv::CommandLineParser parser(argc, argv, "{help h||}{@input|1|}{path|../data/shape_sample/|}");
    if (parser.has("help"))
    {
        help();
        return 0;
    }
    int indexQuery = parser.get<int>("@input");
    if (!parser.check())
    {
        parser.printErrors();
        help();
        return 1;
    }
    path = parser.get<string>("path");
    if (!parser.check())
    {
        parser.printErrors();
        help();
        return 2;
    }

    if (indexQuery < 1 || indexQuery > 20)
    {
        help();
        return 1;
    }
    cv::Ptr  mysc = cv::createShapeContextDistanceExtractor();

    Size sz2Sh(300,300);
    stringstream queryName;
    queryName<".png";
    Mat query=imread(queryName.str(), IMREAD_GRAYSCALE);
    Mat queryToShow;
    resize(query, queryToShow, sz2Sh);
    imshow("QUERY", queryToShow);
    moveWindow("TEST", 0,0);
    vector contQuery = simpleContour(query);
    int bestMatch = 0;
    float bestDis=FLT_MAX;
    for ( int ii=1; ii<=20; ii++ )
    {
        if (ii==indexQuery) continue;
        waitKey(30);
        stringstream iiname;
        iiname<".png";
        cout<<"name: "<0);
        Mat iiToShow;
        resize(iiIm, iiToShow, sz2Sh);
        imshow("TEST", iiToShow);
        moveWindow("TEST", sz2Sh.width+50,0);
        vector contii = simpleContour(iiIm);
        float dis = mysc->computeDistance( contQuery, contii );
        if ( disstd::cout<<" distance between "<" and "<" is: "<std::endl;
    }
    destroyWindow("TEST");
    stringstream bestname;
    bestname<".png";
    Mat iiIm=imread(bestname.str(), 0);
    Mat bestToShow;
    resize(iiIm, bestToShow, sz2Sh);
    imshow("BEST MATCH", bestToShow);
    moveWindow("BEST MATCH", sz2Sh.width+50,0);
    waitKey();

    return 0;
}