#include "cv.h"
#include "highgui.h"
#include <stdio.h>
void PrintMat(CvMat *A);//显示矩阵
void GenRandn(CvMat *arr,int seed);//生成正态分布的随机矩阵
void GenRand(CvMat *arr,int seed);//生成[0,1]均匀分布的随机矩阵
static int cmp_func(const void * _a,const void * _b,void * userdata);//比较函数
void Test_Multiply();//测试矩阵乘法
void Test_cvGetRawData();//将缓存数据填入CvMat数组中
void Test_DCT();//计算DCT变换
void Test_Rand();//生成随机数
void Test_SeqSort();//二维序列排序
int main(void)
{Test_Multiply();Test_cvGetRawData();Test_DCT();Test_Rand();Test_SeqSort();return 0;
}
/*矩阵乘法*/
void Test_Multiply()
{double a[]={1,2,3,4,5,6,7,8,9,10,11,12};double b[]={1,5,9,2,6,10,3,7,11,4,8,12};double c[9];CvMat Ma,Mb,Mc;printf("/n=== Test Multiply ===/n");cvInitMatHeader(&Ma,3,4,CV_64FC1,a,CV_AUTOSTEP);cvInitMatHeader(&Mb,4,3,CV_64FC1,b,CV_AUTOSTEP);cvInitMatHeader(&Mc,3,3,CV_64FC1,c,CV_AUTOSTEP);cvMatMulAdd(&Ma,&Mb,0,&Mc);PrintMat(&Ma);PrintMat(&Mb);PrintMat(&Mc);
}
void Test_cvGetRawData()
{float *data;int step;float a[]={ 1,2,3,4,-5,6,7,8,9,-10,-11,12};CvMat array;CvSize size;int x,y;printf("/n ===Test get raw dara! ===/n");cvInitMatHeader(&array,3,4,CV_32FC1,a,CV_AUTOSTEP);cvGetRawData(&array,(uchar **)&data,&step,&size);//得到矩阵的信息step/=sizeof(data[0]);printf("/nCvMat = ");PrintMat(&array);printf("/nData = ");for (y=0;y<size.height;y++,data+=step){printf("/n");for (x=0;x<size.width;x++){data[x]=(float)fabs(data[x]);printf("%8.2f",data[x]);}printf("/n");}
}
void Test_DCT()
{float data[]={1,2,3,4,5,6,7,8};CvMat a;a = cvMat(2,4,CV_32FC1,data);printf("/n === Test DCT ===");printf("/nOriginal Matrix = ");PrintMat(&a);cvDCT(&a,&a,CV_DXT_FORWARD);printf("/n2-D DCT = ");PrintMat(&a);cvDCT(&a,&a,CV_DXT_INVERSE);printf("/n2-D IDCT = ");PrintMat(&a);
}
void Test_Rand()
{CvMat *a=cvCreateMat(10,6,CV_32F);int i;printf("/n === Test generating random matrix === ");for (i=0;i<5;i++){GenRandn(a,i);PrintMat(a);}cvReleaseMat(&a);
}
void GenRand(CvMat *arr,int seed)
{CvRandState rng;rng.state =cvRNG(0xffffffff);cvRandInit(&rng,0,1,    /* 现在使用虚参数以后再调整 */seed,    /* 使用一个种子  */CV_RAND_UNI    /* 指定为均匀分布类型 */);cvRandArr(&rng.state,arr,CV_RAND_UNI,cvRealScalar(0),cvRealScalar(1));
}
void GenRandn(CvMat *arr,int seed)
{CvRandState rng;rng.state =cvRNG(0xffffffff);cvRandInit(&rng,0,1,    /* 现在使用虚参数以后再调整 */seed,    /* 使用一个种子  */CV_RAND_NORMAL    /* 指定为均匀分布类型 */);cvRandArr(&rng.state,arr,CV_RAND_NORMAL,cvRealScalar(0),cvRealScalar(1));
}
void PrintMat(CvMat *A)
{int i,j;for (i=0;i<A->rows;i++){printf("/n");switch(CV_MAT_DEPTH(A->type)){case CV_32F:case CV_64F:for (j=0;j<A->cols;j++)printf("%9.3f",(float)cvGetReal2D(A,i,j));break;case CV_8U:case CV_16U:for (j=0;j<A->cols;j++)printf("%6d",(int)cvGetReal2D(A,i,j));break;default:break;}}printf("/n");
}
void Test_SeqSort()
{CvMemStorage *storage = cvCreateMemStorage(0);CvSeq *seq=cvCreateSeq(CV_32SC2,sizeof(CvSeq),sizeof(CvPoint),storage);int i;printf("/n=== Test Sequence sorting! === ");for (i=0;i<10;i++){CvPoint pt;pt.x= rand()%1000; // 得到1000以内的随机数pt.y= rand()%1000;cvSeqPush(seq,&pt);//添加元素到序列末尾}printf("/nOriginal point set:/n");for (i=0;i<seq->total;i++){CvPoint *pt =(CvPoint *)cvGetSeqElem(seq,i);printf("(%d,%d)/n",pt->x,pt->y);}cvSeqSort(seq,cmp_func,0);printf("/nAfter sorting: /n");for (i=0;i<seq->total;i++){CvPoint *pt =(CvPoint *)cvGetSeqElem(seq,i);printf("(%d,%d)/n",pt->x,pt->y);}cvClearSeq(seq);cvReleaseMemStorage(&storage);
}
static int cmp_func(const void * _a,const void * _b,void * userdata)
{CvPoint *a=(CvPoint *)_a;CvPoint *b=(CvPoint *)_b;int y_diff=a->y-b->y;int x_diff=a->x-b->x;return y_diff?y_diff:x_diff;
}本文转自gnuhpc博客园博客，原文链接：http://www.cnblogs.com/gnuhpc/archive/2012/07/02/2573824.html，如需转载请自行联系原作者