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x01.Lab.OpenCV: 计算机视觉

时间:2014-05-02 09:56:18      阅读:413      评论:0      收藏:0      [点我收藏+]

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横看成岭侧成峰,计算视觉大不同。观看的角度不同,成像自然不同,这对计算机视觉来说,是个大麻烦。但计算机视觉应用如此广泛,却又有不得不研究的理由。指纹机大家都用过吧,这不过是冰山之一角。产品检测,机器人,医学成像等等,都有计算机视觉的身影。

学习计算机视觉,OpenCV 是个不错的选择。下载安装到指定位置后,会发现有 3.5G 之多。初步看看,重复太多,32位,64位各有一套,而 vc10,vc11,vc12 再次重复。只需把要用到的 build -> x86 -> vc12 调试版提取出来即可。我是编译源代码,将生成的 bin -> *.dll, lib -> *.lib 和原来 OpenCV 安装目录 build -> include 提取出来,放入新建文件夹中,约 60MB。平时学习,使用这个即可。

1.配置系统环境变量,将 bin 加入 Path 变量,注销一下使其有效。

2.启动 VS2013,新建 Win32 Console 空项目。在项目 属性 -> VC++ 目录 -> 包含目录 添加 include库目录 添加 lib

3.新建头文件 x01CV.h,内容如下:

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#pragma once

#pragma comment(lib,"opencv_calib3d249d.lib")
#pragma comment(lib,"opencv_contrib249d.lib")
#pragma comment(lib,"opencv_core249d.lib")
#pragma comment(lib,"opencv_features2d249d.lib")
#pragma comment(lib,"opencv_flann249d.lib")
#pragma comment(lib,"opencv_gpu249d.lib")
#pragma comment(lib,"opencv_highgui249d.lib")
#pragma comment(lib,"opencv_imgproc249d.lib")
#pragma comment(lib,"opencv_legacy249d.lib")
#pragma comment(lib,"opencv_ml249d.lib")
#pragma comment(lib,"opencv_nonfree249d.lib")
#pragma comment(lib,"opencv_objdetect249d.lib")
#pragma comment(lib,"opencv_ocl249d.lib")
#pragma comment(lib,"opencv_photo249d.lib")
#pragma comment(lib,"opencv_stitching249d.lib")
#pragma comment(lib,"opencv_superres249d.lib")
#pragma comment(lib,"opencv_ts249d.lib")
#pragma comment(lib,"opencv_video249d.lib")
#pragma comment(lib,"opencv_videostab249d.lib")

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>    
#include <opencv/cv.h>
x01CV.h

4.新建源文件 Main.cpp,内容如下:

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#include <iostream>
#include "x01CV.h"

using namespace cv;
using namespace std;

namespace
{
    const string AppTitle = "x01 Lab - OpenCV Demo";

    int g_filterValue = 3;
    Mat g_srcImage, g_destImage;    

    void OnBoxFilter(int, void*)
    {
        boxFilter(g_srcImage, g_destImage, -1, Size(g_filterValue + 1, g_filterValue + 1));
        imshow(AppTitle, g_destImage);
    }
    void OnBlur(int, void*)
    {
        blur(g_srcImage, g_destImage, Size(g_filterValue + 1, g_filterValue + 1), Point(-1, -1));
        imshow(AppTitle, g_destImage);
    }
    void OnGaussianBlur(int, void*)
    {
        int v = g_filterValue * 2 + 1;
        GaussianBlur(g_srcImage, g_destImage, Size(v, v), 0, 0);
        imshow(AppTitle, g_destImage);
    }
    void OnMediaBlur(int, void*)
    {
        medianBlur(g_srcImage, g_destImage, g_filterValue * 2 + 1);
        imshow(AppTitle, g_destImage);
    }
    void OnBilateralFilter(int, void*)
    {
        int v = g_filterValue + 7;
        bilateralFilter(g_srcImage, g_destImage, v, v * 2, v / 2);
        imshow(AppTitle, g_destImage);
    }
}

int main()
{
    g_srcImage = imread("1.jpg");

    // For erode and dilate demo
    /*Mat kernel = getStructuringElement(MORPH_RECT, Size(15, 15));
    Mat dest;
    erode(g_srcImage, dest, kernel);

    namedWindow(AppTitle);
    imshow(AppTitle, dest);*/
    
    g_destImage = g_srcImage.clone();

    while (true)
    {
        char c = char(waitKey());
        if (c == q) break;

        namedWindow(AppTitle);
        
        if (c == a || c == A)
            createTrackbar("Kernel Value", AppTitle, &g_filterValue, 40, OnBlur);
        else if (c == b || c == B)
            createTrackbar("Kernel Value", AppTitle, &g_filterValue, 40, OnBoxFilter);
        else if (c == c || c == C)
            createTrackbar("Kernel Value", AppTitle, &g_filterValue, 40, OnGaussianBlur);
        else if (c == d || c == D)
            createTrackbar("Kernel Value", AppTitle, &g_filterValue, 40, OnMediaBlur);
        else if (c == e || c == E)
            createTrackbar("Kernel Value", AppTitle, &g_filterValue, 40, OnBilateralFilter);
        
        imshow(AppTitle, g_destImage);
    }

    return 0;
}
Main.cpp

5.F5 运行无误,按 a 或 b, c, d, e 等,可进行模糊处理。效果图如下:


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x01.Lab.OpenCV: 计算机视觉,布布扣,bubuko.com

x01.Lab.OpenCV: 计算机视觉

标签:des   style   blog   class   code   tar   

原文地址:http://www.cnblogs.com/china_x01/p/3703676.html

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