《学习opencv》笔记——矩阵和图像操作——cvInRange,cvInRangeS,cvInvert and cvMahalonobis

矩阵和图像的操作

(1)cvInRange函数

其结构

void cvInRange(//提取图像中在阈值中间的部分
	const CvArr* src,//目标图像
	const CvArr* lower,//阈值下限
	const CvArr* upper,//阈值上限
	CvArr* dst//结果图像
);

#include <cv.h>
#include <highgui.h>
#include <stdio.h>
#include <iostream>
using namespace std;


int main() 
{ 
	IplImage *src1,*src2,*dst11,*dst12,*dst13,*dst21,*dst22,*dst23;
	src1=cvLoadImage("5.jpg");
	src2=cvLoadImage("7.jpg");
	dst11 = cvCreateImage(cvSize(src1->width, src1->height), IPL_DEPTH_8U, 1);
	dst12 = cvCreateImage(cvSize(src1->width, src1->height), IPL_DEPTH_8U, 1);
	dst13 = cvCreateImage(cvSize(src1->width, src1->height), IPL_DEPTH_8U, 1);
	dst21 = cvCreateImage(cvSize(src2->width, src1->height), IPL_DEPTH_8U, 1);
	dst22 = cvCreateImage(cvSize(src2->width, src1->height), IPL_DEPTH_8U, 1);
	dst23 = cvCreateImage(cvSize(src2->width, src1->height), IPL_DEPTH_8U, 1);
	cvSplit(src1, dst11, dst12, dst13, 0);
	cvSplit(src2, dst21, dst22, dst23, 0);
	
	cvInRange(dst12,dst21,dst23,dst23);
	cvShowImage( "原图", src1);
	cvShowImage("过滤图",src2);
	cvShowImage( "结果图", dst23);

	cvWaitKey();
	return 0;
}

(2)cvInRangeS函数

其结构

void cvInRangeS(//提取图像中在阈值中间的部分
	const CvArr* src,//目标图像
	CvScalar lower,//阈值下限
	CvScalar upper,//阈值上限
	CvArr* dst//结果图像
);

#include <cv.h>
#include <highgui.h>
#include <stdio.h>
#include <iostream>
using namespace std;


int main() 
{ 
	IplImage *src1,*src2,*dst11,*dst12,*dst13,*dst21,*dst22,*dst23;
	src1=cvLoadImage("5.jpg");
	dst11 = cvCreateImage(cvSize(src1->width, src1->height), IPL_DEPTH_8U, 1);
	dst12 = cvCreateImage(cvSize(src1->width, src1->height), IPL_DEPTH_8U, 1);
	dst13 = cvCreateImage(cvSize(src1->width, src1->height), IPL_DEPTH_8U, 1);

	CvScalar cs1;
	cs1.val[0] = 0;
	cs1.val[1] = 0;
	cs1.val[2] = 0;
	cs1.val[3] = 0;
	CvScalar cs2;
	cs2.val[0] = 80;
	cs2.val[1] = 0;
	cs2.val[2] = 0;
	cs2.val[3] = 0;

	cvSplit(src1, dst11, dst12, dst13, 0);

	cvInRangeS(dst11,cs1,cs2,dst13);
	cvShowImage( "原图", src1);
	cvShowImage( "变单通过程图", dst11);
	cvShowImage( "结果图", dst13);

	cvWaitKey();
	return 0;
}

(3)cvInvert函数

其结构

double cvInvert(//矩阵取逆
	const CvArr* src,//目标矩阵
	CvArr* dst,//结果矩阵
	int method = CV_LU//逆运算方法
);

#include <cv.h>
#include <highgui.h>
#include <stdio.h>
#include <iostream>
using namespace std;


int main() 
{ 
		double a[3][3] = 
		{    
			{1,0,0},
			{0,2,0},
			{0,0,3}
		};

		CvMat va = cvMat(3,3, CV_64FC1,a);

		cout<<"目标矩阵："<<endl;

		for(int i=0;i<3;i++)
		{
			for(int j=0;j<3;j++)
				printf("%f\t",cvmGet(&va,i,j));
			cout << endl;
		}


		cvInvert(&va,&va);

		cout << "其逆矩阵为：";
		cout<<endl;
		for(int i=0;i<3;i++)
		{
			for(int j=0;j<3;j++)
				printf("%f\t",cvmGet(&va,i,j));
			cout << endl;
		}
		getchar();
		return 0;
	
}

(4)cvMahalonobis函数

其结构

CvSize cvMahalonobis(//计算马氏距离
	const CvArr* vec1,//样本向量
	const CvArr* vec2,//平均值
	CvArr* mat//协方差的逆
);

ps：关于什么是马氏向量，我也研究了半天，找了一些资料算是弄明白了个大概。

        关于马氏距离，定义的话自己百度百科就行。

关于理解和解释请参照博客：点击打开链接 通俗易懂

关于下面的代码实例的数据来源：点击打开链接

实例代码

#include <cv.h>
#include <highgui.h>
#include <stdio.h>
#include <iostream>
using namespace std;

int main() 
{ 
		double a1[4] = {3,4,5,6};
		double a2[4] = {2,2,8,4};
		
		double b[4] = {2.5, 3, 6.5, 5};

		double c[4][4] =
		{
				{0.25,0.50,-0.75,0.50},
				{0.50,1.00,-1.50,1.00},
				{-0.75,-1.50,2.25,-1.50},
				{0.50,1.00,-1.50,1.00}
	     };
		CvMat va1 = cvMat(1,4, CV_64FC1,a1);
		CvMat va2 = cvMat(1,4, CV_64FC1,a2);
		CvMat vb = cvMat(1,4, CV_64FC1,b);
		CvMat vc = cvMat(4,4, CV_64FC1,c);

		cvInvert(&vc,&vc,CV_SVD); //协方差取逆，这个函数前面讲过

		double r1 = cvMahalanobis(&va1,&vb,&vc);
		double r2 = cvMahalanobis(&va2,&vb,&vc);
		cout << "样本1的马氏距离："<<endl;
		cout<<r1<<endl;
		cout << "样本2的马氏距离："<<endl;
		cout<<r2<<endl;
		
		getchar();
		return 0;	
}

to be continued

《学习opencv》笔记——矩阵和图像操作——cvInRange,cvInRangeS,cvInvert and cvMahalonobis,布布扣,bubuko.com

《学习opencv》笔记——矩阵和图像操作——cvInRange,cvInRangeS,cvInvert and cvMahalonobis

原文：http://blog.csdn.net/zhurui_idea/article/details/28630589