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ImgPro.cpp
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/**
该头文件使用OpenCV库实现读取图片并保存像素信息、直接输出一幅图片、对图像进行一些常见处理操作。
@author : webary
@time (last update time): 2014.9.2 23:00
**/
#include "stdafx.h"
#ifdef __AFXWIN_H__
#include"ImgPro.h"
#else
#include<windows.h>
#include<iostream>
#include<iomanip>
#include<cstdlib>
#include<cstdio>
#include<string>
#include<cv.h>
#include<highgui.h>
#include"opencv2/legacy/legacy.hpp" //openCV 2.3上的目录,支持函数cvCalcPGH
using namespace std;
typedef const char cchar;
typedef const IplImage CIplImage;
#ifndef _IMGPRO_H_VAR_
#define _IMGPRO_H_VAR_
extern int width, height, depth;
extern IplImage *pimg, *pGray;
extern char info[10000];
extern IplImage* find_obj_match;
#endif
IplImage *loadImg(cchar* tmpimgName,int ask=1,int cls=1,int color=1,int show=1);
#ifdef __AFXWIN_H__
IplImage *loadImg(CString tmpimgstring,int ask=1,int cls=1,int color=1,int show=1);
void Screen(char *filename="");
#endif
void saveRGB( IplImage* img = pimg,cchar *fileOutName = 0) ;
void outputImg(cchar* imgOutName,int readAgain = 1,IplImage* img = pimg) ;
void saveIplImage(IplImage* img = pimg);
void saveImg(cchar* imgSaveName,CIplImage* img = pimg);
int showImg(CIplImage* img = pimg,cchar* str = "图片显示",cchar* ss="显示图像出错",int pause=1) ;
void releaseImg(IplImage** ppimg = &pimg) ;
CvSeq* findContour(CIplImage* src,IplImage** dst=0,int th=100,int filled=0) ;
double find_obj(cchar* imgName,cchar* objName,int showInfo=0
,int showMatch=0,int showSurf=0);
void matchWeight(CIplImage* img1, CIplImage* img2,double* wm,int show=0,int n=20,int m=20);
void Hilditch(CIplImage* src,IplImage* dst=0,int th=128,int maxIterations=-1);
float Entropy(CIplImage* img=pimg,int th=1,int w=0,int h=0);
#endif
#if !b_multiThread
uchar R[MAXSIZE][MAXSIZE], G[MAXSIZE][MAXSIZE], B[MAXSIZE][MAXSIZE], **A;
IplImage *pimg=0, *pGray=0;
int width=0, height=0, depth=0;
#endif
char info[10000] = "";
//载入图片
#ifndef _MSC_VER
#include<io.h> //access()
IplImage *loadImg(cchar* tmpimgName,int ask,int cls,int color,int show)
{
if(tmpimgName==0 || tmpimgName[0]==0)
return 0;
char imgName[200], tempName[200];
strcpy(imgName,tmpimgName);
int first = 1,flag;
IplImage * img=0;
do
{
flag = 0;
if(first==0)
{
cout<<"请输入需要载入的图片: ";
gets(imgName);
}
if(access(imgName,4)) //打开失败,没有读取权限
{
strcpy(tempName,imgName);
if(strstr(tempName,".jpg")==0) //文件名没有以.jpg结尾
{
strcat(tempName,".jpg");
if(access(tempName,1)) //打开失败,没有读取权限
{
strcpy(tempName,imgName);
if(strstr(tempName,".png")==0) //文件名没有以.png结尾
{
strcat(tempName,".png");
if(access(tempName,1)) //打开失败,没有读取权限
{
strcpy(tempName,imgName);
if(strstr(tempName,".bmp")==0) //文件名没有以.bmp结尾
{
strcat(tempName,".bmp");
if(access(tempName,1)==0)
strcpy(imgName,tempName);
}
}
else
strcpy(imgName,tempName);
}
}
else
strcpy(imgName,tempName);
}
if(access(imgName,1)) //打开失败,没有读取权限
{
if(first)
{
first = 0;
flag = 1;
continue;
}
cout<<"打开图片 \""<<imgName<<"\" 失败 ！"<<endl;
flag = 1;
}
}
if(access(imgName,1)==0 && (strstr(imgName,".jpg") || strstr(imgName,".bmp") || strstr(imgName,".png"))) //图片可以读取
{
img = cvLoadImage(imgName,color);
if(cls) system("cls");
char tips[200] = "已成功载入图片 ";
strcat(tips,imgName);
if(show) cout<<tips<<endl;
if(first && ask && MessageBox(NULL,"是否重新载入其他图片？",tips,MB_YESNO)==IDYES)
{
if(cls) system("cls");
flag = 1;
}
}
first = 0;
}
while(flag);
if(show)
cout<<"width(宽) : "<<img->width<<" height(高) : "<<img->height<<endl;
// <<" depth(位深度) : "<<img->depth
width = img->width;
height = img->height;
depth = img->depth;
pimg = img;
return img;
}
#else
#include"Shlwapi.h" //PathFileExists()
#pragma comment(lib,"shlwapi.lib")
IplImage *loadImg(cchar* tmpimgName,int ask/*=1*/,int cls/*=1*/,int color/*=1*/,int show/*=1*/)
{
if(tmpimgName==0 || tmpimgName[0]==0)
return 0;
char imgName[200], tempName[200];
strcpy(imgName,tmpimgName);
int first = 1,flag;
IplImage * img=0;
do
{
flag = 0;
if(first==0)
{
CString warn;
warn.Format(_T("无法载入\"%s\",请先指定正确的图像路径，然后载入图像"),tmpimgName);
MessageBox(NULL,warn,"载入图像失败",MB_ICONERROR);
return 0;
}
if(!PathFileExists(imgName)) //打开失败,没有读取权限
{
strcpy(tempName,imgName);
if(strstr(tempName,".jpg")==0) //文件名没有以.jpg结尾
{
strcat(tempName,".jpg");
if(!PathFileExists(tempName)) //打开失败,没有读取权限
{
strcpy(tempName,imgName);
if(strstr(tempName,".png")==0) //文件名没有以.png结尾
{
strcat(tempName,".png");
if(!PathFileExists(tempName)) //打开失败,没有读取权限
{
strcpy(tempName,imgName);
if(strstr(tempName,".bmp")==0) //文件名没有以.bmp结尾
{
strcat(tempName,".bmp");
if(PathFileExists(tempName))//文件可访问
strcpy(imgName,tempName);
}
}
else
strcpy(imgName,tempName);
}
}
else
strcpy(imgName,tempName);
}
if(!PathFileExists(imgName)) //打开失败,没有读取权限
{
flag = 1;
if(first)
{
first = 0;
continue;
}
sprintf(info,"%s打开图片 \"%s\" 失败 ！\r\n",info,imgName);
MessageBox(NULL,"打开图像失败","出错提示",0);
}
}
if(PathFileExists(imgName) && (strstr(imgName,".jpg") || strstr(imgName,".bmp") || strstr(imgName,".png"))) //图片可以读取
{
img = cvLoadImage(imgName,color);
if(show)
{
char tips[200] = "已成功载入图像文件 ";
strcat(tips,imgName);
sprintf(info,"%s%s\r\n",info,tips);
}
}
else
flag = 1;
first = 0;
}
while(flag);
if(show)
sprintf(info,"%swidth(宽) : %d height(高) : %d\r\n",info,img->width,img->height);
#if !b_multiThread
width = img->width;
height = img->height;
depth = img->depth;
pimg = img;
#endif
return img;
}
#ifdef __AFXWIN_H__
IplImage *loadImg(CString tmpimgstring,int ask/*=1*/,int cls/*=1*/,int color/*=1*/,int show/*=1*/)
{
return loadImg((LPSTR)(LPCTSTR)tmpimgstring,ask,cls,color,show);
}
#endif //__AFXWIN_H__
#endif //_MSC_VER
//输出图片到本地文件，第二个参数是选择是否再次读取RGB值---非线程安全（readAgain为真时）
void outputImg(cchar* imgOutName,int readAgain/* = 1*/,IplImage* img/* = pimg*/)
{
if(imgOutName[0]==0 || img==0)
return;
if(readAgain)
#if b_multiThread
MessageBox(0,"已开启多线程，无法使用线程不安全的全局变量","读取全局变量失败",0);
#else
saveIplImage(img);
#endif
if (strstr(imgOutName, ".jpg") == 0 && strstr(imgOutName, ".bmp") == 0 && strstr(imgOutName, ".png") == 0)
{
char name[200];
strcpy(name,imgOutName);
strcat(name,".jpg");
cvSaveImage(name,img);
}
else
cvSaveImage(imgOutName,img);
}
//保存图片到文件---此函数线程安全（默认readAgain为假）
void saveImg(cchar* imgSaveName,IplImage* img)
{
outputImg(imgSaveName,0,img);
}
//保存图片像素信息到文件或数组---非线程安全（使用了全局变量RGB）
void saveRGB( CIplImage* img/* = pimg*/,cchar *fileOutName/* = 0*/)
{
if(img==0)
return;
uchar* data = (uchar*)img->imageData;
if(fileOutName && fileOutName[0])
{
FILE *fp1;
if(fp1 = fopen(fileOutName,"w"))
{
if(img->nChannels==3)
{
for( int y = 0; y < img->height; y++ )
for( int x = 0,yy = y * img->widthStep; x < img->width; x++ )
fprintf(fp1,"%d\t%d\t%d\n",data[yy+3*x+2],data[yy+3*x+1],data[yy+3*x]);
}
else if(img->nChannels==1)
{
for( int y = 0; y < img->height; y++ )
for( int x = 0,yy = y * img->widthStep; x < img->width; x++ )
fprintf(fp1,"%d\n",data[yy+x]);
}
fclose(fp1);
}
}
else
{
#if b_multiThread
MessageBox(0,"已开启多线程，无法使用线程不安全的全局变量","读取全局变量失败",0);
#else
if(img->nChannels==3)
{
for( int y = 0; y < img->height; y++ )
for( int x = 0,yy = y * img->widthStep; x < img->width; x++ )
{
R[y][x] = data[yy+3*x+2];
G[y][x] = data[yy+3*x+1];
B[y][x] = data[yy+3*x];
}
}
else if(img->nChannels==1)
{
for( int y = 0; y < img->height; y++ )
for( int x = 0,yy = y * img->widthStep; x < img->width; x++ )
R[y][x] = data[yy+x];
}
#endif
}
}
//保存当前的RGB数组到IplImage指针中---非线程安全
void saveIplImage(IplImage* img/* = pimg*/)
{
#if b_multiThread
MessageBox(0,"已开启多线程，无法使用线程不安全的全局变量","读取全局变量失败",0);
#else
uchar* data = (uchar*)img->imageData;
if(img->nChannels==3)
{
for( int y = 0; y < img->height; y++ )
for( int x = 0,yy = y * img->widthStep; x < img->width; x++ )
{
data[yy+3*x+2] = R[y][x];
data[yy+3*x+1] = G[y][x];
data[yy+3*x] = B[y][x];
}
}
else if(img->nChannels==1)
{
for( int y = 0; y < img->height; y++ )
for( int x = 0,yy = y * img->widthStep; x < img->width; x++ )
data[yy+x] = R[y][x];
}
#endif
}
//得到某一个像素点的灰度值---非线程安全
inline unsigned char getGray(int i,int j)
{
#if b_multiThread
MessageBox(0,"已开启多线程，无法使用线程不安全的全局变量","读取全局变量失败",0);
return 0;
#else
//return (.3*R[i][j]+.6*G[i][j]+.1*B[i][j]+1)/3;
if(pimg->nChannels==3)
return (R[i][j]+G[i][j]+B[i][j]+1)/3;
else
return R[i][j];
#endif
}
//像素取反---非线程安全
void reverseRGB(int th=255)
{
#if b_multiThread
MessageBox(0,"已开启多线程，无法使用线程不安全的全局变量","读取全局变量失败",0);
#else
for(int i=0; i<height; i++)
for(int j=0; j<width; j++)
{
R[i][j] = R[i][j]>th?0 : 255 - R[i][j];
G[i][j] = G[i][j]>th?0 : 255 - G[i][j];
B[i][j] = B[i][j]>th?0 : 255 - B[i][j];
}
#endif
}
//灰度化图像---非线程安全
void grayRGB()
{
#if b_multiThread
MessageBox(0,"已开启多线程，无法使用线程不安全的全局变量","读取全局变量失败",0);
#else
for(int i=0; i<height; i++)
for(int j=0; j<width; j++)
R[i][j]=G[i][j]=B[i][j] = getGray(i,j);
#endif
}
//控制并滤除偏白（亮度较高）的噪声点---非线程安全
void controlWhtieNoise(int th)
{
#if b_multiThread
MessageBox(0,"已开启多线程，无法使用线程不安全的全局变量","读取全局变量失败",0);
#else
//另一种思想：if(R[i][j]>th && G[i][j]>th && B[i][j]>th)
for(int i=0; i<height; i++)
for(int j=0; j<width; j++){
if(pimg->nChannels==3) {
int sum = (int)R[i][j]+G[i][j]+B[i][j];
if(sum>3*th)
R[i][j] = G[i][j] = B[i][j] = (uchar)255;
else
R[i][j] = G[i][j] = B[i][j] = (uchar)((sum+1)/3);
}else if(R[i][j]>th)
R[i][j] = (uchar)255;
}
#endif
}
//显示图片
int showImg(CIplImage* img/* = pimg*/, cchar* str/* = "图片显示"*/, cchar* ss/*"显示图像出错"*/, int pause/*=1*/)
{
if(img==0)
{
#ifdef __AFXWIN_H__
MessageBox(NULL,"图像指针无效，请先载入有效图像后再使用该功能",ss,MB_ICONSTOP);
#endif
return 0;
}
cvNamedWindow(str);
cvShowImage(str,img);
if(pause==1)
{
cvWaitKey(0);
cvDestroyWindow(str);//销毁窗口
}
return 1;
}
void showImg(cchar *file)
{
if(strstr(file,".jpg")==0 && strstr(file,".bmp")==0 && strstr(file,".png")==0)
{
char name[200];
strcpy(name,file);
strcat(name,".jpg");
system(name);
}
else
system(file);
}
//释放图片内存指针
void releaseImg(IplImage** ppimg/* = &pimg*/)
{
if(*ppimg)
{
cvReleaseImage(ppimg);
*ppimg = 0;
}
}
//从文件夹读取所有图片
void readBMPFromFolder(const char* fileFolder,char readPath[100][300],int del=1)
{
char str[300] = "DIR /s /b /o:e "; // /s得到并列文件夹以及子文件夹下所有图片
strcat(str,fileFolder);
strcat(str," > fileList.txt");
system(str); // 保存该文件夹下所有文件到fileList.txt
int i = 0,flag = 1; // flag为文件结束标识;
freopen("fileList.txt","r",stdin); //输入重定向至文本文件
while(1)
{
char filePath[200] = " ";
while(strstr(filePath,".bmp")==0
&&strstr(filePath,".jpg")==0
&&strstr(filePath,".png")==0)
if(gets(filePath)==NULL)
{
flag = 0; // 文件已读完，直接中止
break;
}
if(flag==0) break;
strcpy(readPath[i++],filePath); //得到该图像的绝对路径
}
freopen("CON", "r", stdin ); //输入重定向至控制台
if(del)
remove("fileList.txt");
}
//最大类间方差算法 将灰度图像灰度级分割(注意:传入的需要是灰度图像数据)
int Otsu(CIplImage* src)
{
int height=src->height, width=src->width, threshold, i, j;
double histogram[256] = {0};
for(i=0; i < height; i++)
{
uchar* p=(uchar*)src->imageData + src->widthStep * i;
for(j = 0; j < width; j++)
histogram[*p++]++;
}
int size = height * width;
for(i = 0; i < 256; i++)
histogram[i] /= size;
double avgValue=0, maxVariance=0, w = 0, u = 0;
for(i=0; i < 256; i++)
avgValue += i * histogram[i]; //整幅图像的平均灰度
for(i = 0; i < 256; i++)
{
w += histogram[i];
u += i * histogram[i];
double t = avgValue * w - u;
double variance = t * t / (w * (1 - w) );
if(variance > maxVariance)
{
maxVariance = variance;
threshold = i;
}
}
return threshold;
}
//将图片直方图均衡化处理--利用cv库函数--需要释放该指针
IplImage* equalizeHist(CIplImage* img, int saveFile/*=0*/)
{
if(img==0)
return 0;
IplImage* pGray = cvCreateImage(cvGetSize(img),img->depth,1);
if(img->nChannels==3)
cvCvtColor(img,pGray,CV_BGR2GRAY);
else if(img->nChannels==1)
cvCopy(img,pGray);
else
{
releaseImg(&pGray);
return 0;
}
cvEqualizeHist(pGray,pGray);
if(saveFile)
outputImg("均衡化.jpg",0,pGray);
return pGray;
}
//将图片直方图均衡化处理--利用自编函数--需要释放该指针
IplImage* Histeq(CIplImage* img, int saveFile = 0)
{
if(img==0)
return 0;
IplImage* pGray = cvCreateImage(cvGetSize(img),img->depth,1);
if(img->nChannels==3)
cvCvtColor(img,pGray,CV_BGR2GRAY);
else if(img->nChannels==1)
cvCopy(img,pGray);
else
{
releaseImg(&pGray);
return 0;
}
double histogram[256] = {0},dTemp;
int i,j,k;
uchar* p;
for(i=0; i < pGray->height; i++)
{
p=(uchar*)pGray->imageData + pGray->widthStep * i;
for(j = 0; j < pGray->width; j++)
histogram[*p++]++;
}
int size = pGray->height * pGray->width;
for(i = 0; i < 256; i++)
histogram[i] /= size;
for(i=0; i < pGray->height; i++)
{
p=(uchar*)pGray->imageData + pGray->widthStep * i;
for(j = 0; j < pGray->width; j++)
{
dTemp = 0;
int gray = getGray(i,j);
for(k=0; k<gray; ++k)
dTemp += histogram[k];
int tar = int(255 * dTemp+.5);
if(tar<0) tar = 0;
else if(tar>255) tar = 255;
*p++ = tar;
}
}
if(saveFile)
outputImg("均衡化.jpg",0,pGray);
return pGray;
}
//将图片直方图均衡化处理--结果保存在自身指针中
void Histeq_self(IplImage** ppimg,int save)
{
IplImage* img = *ppimg;
saveRGB(img);
controlWhtieNoise(Otsu(img));//更改RGB：用自动阈值去噪
reverseRGB(); //取反RGB
saveIplImage(img); //将RGB保存到图像指针
IplImage* gray = equalizeHist(img); //均衡化
gray = equalizeHist(gray);//目标是黑色点则再进行一次均衡化
saveRGB(gray);
reverseRGB();
saveIplImage(gray);
if(save)
outputImg("histeq",0,gray);
releaseImg(ppimg);
*ppimg=gray;
}
//计算图片的轮廓
CvSeq* findContour(CIplImage* src, IplImage** dst, int th, int filled)
{
int releaseDst = 0;
if(dst==0) // 没有传递二级指针进入该函数
{
releaseDst = 1;
IplImage* ddst = cvCreateImage(cvSize(src->width,src->height),8,1);
dst = &ddst;
}
else if(*dst==0) // 传递的二级指针没有初始化为图像指针
*dst = cvCreateImage(cvSize(src->width,src->height),8,1);
if(src->nChannels==3)
cvCvtColor(src,*dst,CV_BGR2GRAY);
else
cvCopy(src,*dst);
CvMemStorage *storage = cvCreateMemStorage();
if(th==-1)
{
int getTh(CIplImage*);
th = getTh(src);
}
//cvSmooth(*dst,*dst,CV_MEDIAN,3,3,0,0); //3x3中值滤波
cvCanny(*dst,*dst,th,th);
CvSeq *contour = NULL;
cvFindContours(*dst,storage,&contour); //在二值图像中寻找轮廓
cvThreshold(*dst,*dst,th,255,CV_THRESH_BINARY); //对图像进行固定阈值操作
if(filled)
cvDrawContours(*dst,contour,cvScalarAll(255),cvScalarAll(200),0,CV_FILLED);
else
cvDrawContours(*dst,contour,cvScalarAll(255),cvScalarAll(200),1);
if(releaseDst)
releaseImg(dst);
return contour;
}
//计算图片的7个Hu不变量
double* getHu(CIplImage* src, int th, int printHu, int show, int save, IplImage* dst)
{
if(src==0)
return 0;
int delDst = 0;
if(dst==0)
{
dst = cvCreateImage(cvSize(src->width,src->height),8,1);
delDst = 1;
}
CvSeq *contour = findContour(src,&dst,th);
CvMoments moments;
static CvHuMoments hu; //局部变量作为返回值不安全,故设置为静态变量
cvMoments(dst,&moments,1); //计算多边形和光栅形状的最高达三阶的所有矩
cvGetHuMoments(&moments, &hu); //计算7个Hu不变量
cvDrawContours(dst,contour,cvScalar(255),cvScalar(200),1);
cvReleaseMemStorage(&contour->storage);
for(int i = 0; i<7; ++i)
((double*)&hu)[i] = fabs(log(fabs( ((double*)&hu)[i] )));
//显示7个矩(取对数后的结果)
if(printHu)
{
cout<<setprecision(4);
for(int i = 0; i<7; ++i)
cout<<((double*)&hu)[i]<<"\t";
cout<<"\n";
}
//显示图片
if(show)
showImg(dst,"dst");
//保存图片
if(save)
outputImg("轮廓.jpg",0,dst);
if(delDst)
cvReleaseImage(&dst);
return (double*)&hu;
}
//保存得到的Hu矩值
void saveHu(const double* hu,cchar* path,cchar* file = "hu.txt",int th=-1)
{
FILE* fp = fopen(file,"a");
fprintf(fp,"%-16s",path);
for(int i=0; i<7; i++)
fprintf(fp,"%.2lf\t",hu[i]);
if(th != -1)
fprintf(fp,"阈值: %d",th);
fprintf(fp,"\n");
fclose(fp);
}
//计算两个Hu矩的距离
double comHu(CIplImage* src, CIplImage* dst, int th = 100)
{
return cvMatchShapes(findContour(src,0,th),findContour(dst,0,th),CV_CONTOURS_MATCH_I3);
}
double comHu(const CvSeq *contour1,CIplImage* dst,int th=100)
{
return cvMatchShapes(contour1,findContour(dst,0,th),CV_CONTOURS_MATCH_I3);
}
double comHu(const double* h1,const double* h2)
{
if(h1==0 || h2==0)
return 0;
double dif = 0;
for(int i=0; i<7; i++)
dif += fabs(((h1[i]-h2[i]))/ h1[i]);
return dif;
}
//通过调节滑块得到最好阈值
bool first;
CIplImage* p_image=NULL;
void on_trackbar(int g_thresh) //回调函数
{
static IplImage* p_gray=0;
if(first)
p_gray = cvCreateImage(cvGetSize(p_image),8,1);
CvSeq* contours=findContour(p_image,&p_gray,g_thresh);
cvZero(p_gray);
if(contours)
cvDrawContours(p_gray,contours,cvScalarAll(255),cvScalarAll(200),1);//画轮廓
cvShowImage("调整阈值",p_gray);
first = 0;
cvReleaseImage(&p_gray);
}
int getTh(CIplImage* src)
{
first = 1;
p_image = src;
int g_thresh=100; //初始阈值
cvNamedWindow("调整阈值",1);
cvCreateTrackbar("threshold","调整阈值",&g_thresh,255,on_trackbar);
on_trackbar(g_thresh);
cvWaitKey();
return g_thresh;
}
//计算轮廓的pair-wise几何直方图
CvHistogram* gesCalcContoursPGH(const CvSeq* contour)
{
CvContour* tempCont = (CvContour*)contour;//得到成对几何直方图第二个维度上的范围
cvBoundingRect(tempCont, 1);
int sizes[2] = {60, 200};
float ranges[2][2] = {{0,3.14159f}, {0,200}};
float** rangesPtr = new float* [2];
rangesPtr[0] = ranges[0];
rangesPtr[1] = ranges[1];
//初始化几何直方图
CvHistogram* hist = cvCreateHist(2, sizes, CV_HIST_ARRAY, rangesPtr, 1);
//计算轮廓的成对几何直方图
cvCalcPGH(contour, hist);//计算轮廓的 pair-wise 几何直方图
delete []rangesPtr;
return hist;
}
//对轮廓的pair-wise几何直方图进行匹配
double getMatchContoursPGH(const CvSeq* contour1, const CvSeq* contour2)
{
//得到轮廓的成对几何直方图
CvHistogram* hist1 = gesCalcContoursPGH(contour1);
CvHistogram* hist2 = gesCalcContoursPGH(contour2);
//归一化直方图
cvNormalizeHist(hist1,1);
cvNormalizeHist(hist2,2);
//直方图匹配
double result = cvCompareHist(hist1, hist2, CV_COMP_INTERSECT);
//释放内存
cvReleaseHist(&hist1);
cvReleaseHist(&hist2);
return result;
}
// 将一幅图缩放和旋转变换后保存到另一幅图中
void imRotate(CIplImage *src,IplImage *&dst,double angle,double scale=1,CvPoint2D32f center=cvPoint2D32f(-1,-1))
{
if(dst==0)
{
return;
}
if(src->width == dst->width && src->height == dst->height
&&src->depth == dst->depth &&src->nChannels == dst->nChannels)
{
CvMat *mapMatrix = cvCreateMat(2,3,CV_32FC1);
if(center.x==-1 && center.y==center.x)
center = cvPoint2D32f(src->width/2,src->height/2);
cv2DRotationMatrix(center,angle,scale,mapMatrix);//计算二维旋转的仿射变换矩阵
cvWarpAffine(src,dst,mapMatrix); //对图像做仿射变换
}
else
#ifndef __AFXWIN_H__
cout<<"两幅图类型或规格不一致,无法进行转化"<<endl;
#else
sprintf(info,"%s两幅图类型或规格不一致,无法进行转化\r\n",info);
#endif
}
//下面几个函数一起完成surf角点检测功能，并返回匹配对比例数(外部调用find_obj函数)
//比较surf特征
double compareSURFDescriptors( const float* d1, const float* d2, double best, int length )
{
double total_cost = 0;
assert( length % 4 == 0 );
for( int i = 0; i < length; i += 4 )
{
double t0 = d1[i ] - d2[i ];
double t1 = d1[i+1] - d2[i+1];
double t2 = d1[i+2] - d2[i+2];
double t3 = d1[i+3] - d2[i+3];
total_cost += t0*t0 + t1*t1 + t2*t2 + t3*t3;
if( total_cost > best )
break;
}
return total_cost;
}
//找到单纯最近邻近点
int naiveNearestNeighbor( const float* vec, int laplacian,const CvSeq* model_keypoints,const CvSeq* model_descriptors )
{
int length = (int)(model_descriptors->elem_size/sizeof(float));
int i, neighbor = -1;
double d, dist1 = 1e6, dist2 = 1e6;
CvSeqReader reader, kreader;
cvStartReadSeq( model_keypoints, &kreader, 0 );
cvStartReadSeq( model_descriptors, &reader, 0 );
for( i = 0; i < model_descriptors->total; i++ )
{
const CvSURFPoint* kp = (const CvSURFPoint*)kreader.ptr;
const float* mvec = (const float*)reader.ptr;
CV_NEXT_SEQ_ELEM( kreader.seq->elem_size, kreader );
CV_NEXT_SEQ_ELEM( reader.seq->elem_size, reader );
if( laplacian != kp->laplacian )
continue;
d = compareSURFDescriptors( vec, mvec, dist2, length );
if( d < dist1 )
{
dist2 = dist1;
dist1 = d;
neighbor = i;
}
else if ( d < dist2 )
dist2 = d;
}
if ( dist1 < 0.6*dist2 )
return neighbor;
return -1;
}
//寻找匹配对
void findPairs( const CvSeq* objectKeypoints, const CvSeq* objectDescriptors,
const CvSeq* imageKeypoints, const CvSeq* imageDescriptors, vector<int>& ptpairs )
{
int i;
CvSeqReader reader, kreader;
cvStartReadSeq( objectKeypoints, &kreader );
cvStartReadSeq( objectDescriptors, &reader );
ptpairs.clear();
for( i = 0; i < objectDescriptors->total; i++ )
{
const CvSURFPoint* kp = (const CvSURFPoint*)kreader.ptr;
const float* descriptor = (const float*)reader.ptr;
CV_NEXT_SEQ_ELEM( kreader.seq->elem_size, kreader );
CV_NEXT_SEQ_ELEM( reader.seq->elem_size, reader );
int nearest_neighbor = naiveNearestNeighbor( descriptor, kp->laplacian, imageKeypoints, imageDescriptors );
if( nearest_neighbor >= 0 )
{
ptpairs.push_back(i);
ptpairs.push_back(nearest_neighbor);
}
}
}
//surf匹配
IplImage* find_obj_match = 0;
double find_obj(CIplImage* object, CIplImage* image, int showInfo, int showMatch, int showSurf)
{
if(object->nChannels!=1)
{
#ifndef __AFXWIN_H__
cout<<"#error: 对比图不是单通道图像"<<endl;
#else
sprintf(info,"%s#error: 对比图不是单通道图像\r\n",info);
#endif
return -1;
}
if(image->nChannels!=1)
{
#ifndef __AFXWIN_H__
cout<<"#error: 模板图不是单通道图像"<<endl;
#else
sprintf(info,"%s#error: 模板图不是单通道图像\r\n",info);
#endif
return -1;
}
CvMemStorage* storage = cvCreateMemStorage(0);
IplImage* object_color = cvCreateImage(cvGetSize(object), 8, 3);
cvCvtColor( object, object_color, CV_GRAY2BGR );
CvSeq* objectKeypoints = 0, *objDescriptors = 0;
CvSeq* imageKeypoints = 0, *imageDescriptors = 0;
int i;
int64 tt = cvGetTickCount();
CvSURFParams params = cvSURFParams(800, 1);
cvExtractSURF( object, 0, &objectKeypoints, &objDescriptors, storage, params );
Sleep(1);
cvExtractSURF( image, 0, &imageKeypoints, &imageDescriptors, storage, params );
if(showInfo)
{
#ifndef __AFXWIN_H__
cout<<"Object Descriptors: "<<objDescriptors->total<<"\nImage Descriptors: "<<imageDescriptors->total<<endl;
cout<<"Extraction time = "<<(cvGetTickCount()-tt)/(cvGetTickFrequency()*1000.)<<"ms\n";
#else
sprintf(info,"%sObject Descriptors: %d \tImage Descriptors: %d \t",info,objDescriptors->total,imageDescriptors->total);
sprintf(info,"%sExtraction time = %gms\r\n",info,(cvGetTickCount()-tt)/(cvGetTickFrequency()*1000.));
#endif
}
int max_width = image->width>object->width ? image->width : object->width;
IplImage* correspond = cvCreateImage(cvSize(max_width,object->height+image->height),object->depth,object->nChannels);
cvSetImageROI( correspond, cvRect( 0, 0, object->width, object->height ) );
cvCopy( object, correspond );
cvSetImageROI(correspond,cvRect(0,object->height,image->width,correspond->height));
cvCopy( image, correspond );
cvResetImageROI( correspond );
vector<int> ptpairs;
findPairs(objectKeypoints,objDescriptors,imageKeypoints,imageDescriptors,ptpairs);
if(showMatch)
{
find_obj_match = cvCreateImage(cvGetSize(correspond), 8, 3);
cvCvtColor( correspond, find_obj_match, CV_GRAY2BGR );
}
srand((unsigned)time(NULL));
int matchNum = 0;
double rt_w = object->width/(image->width+.01);
double rt_h = object->height/(image->height+.01);
double error = 0.13;
//cout<<error*rt_w<<" "<<error*rt_h<<endl;
for( i = 0; i < (int)ptpairs.size(); i += 2 )
{
CvScalar cs = {rand()%256,rand()%256,rand()%256};
CvSURFPoint* r1 = (CvSURFPoint*)cvGetSeqElem( objectKeypoints, ptpairs[i] );
CvSURFPoint* r2 = (CvSURFPoint*)cvGetSeqElem( imageKeypoints, ptpairs[i+1] );
if( fabs(r1->pt.x/(r2->pt.x+.01)-rt_w) < error*rt_w
&&fabs(r1->pt.y/(r2->pt.y+.01)-rt_h) < error*rt_h )
{
//cout<<fabs(r1->pt.x/(r2->pt.x+.01)-rt_w)<<" "<<fabs(r1->pt.y/(r2->pt.y+.01)-rt_h)<<endl;
if(showMatch)
cvLine( find_obj_match, cvPointFrom32f(r1->pt), cvPoint(cvRound(r2->pt.x),
cvRound(r2->pt.y+object->height)), cs);
matchNum++;
}
}
if(showSurf)
{
CvScalar red = {0,0,255};
for( i = 0; i < objectKeypoints->total; i++ )
{
CvSURFPoint* r = (CvSURFPoint*)cvGetSeqElem( objectKeypoints, i );
CvPoint center = {cvRound(r->pt.x), cvRound(r->pt.y)};
int radius = cvRound(r->size*1.2/9.*2);
cvCircle( object_color, center, radius, red, 1, 8, 0 );
}
cvNamedWindow("Object", 1);
cvShowImage( "Object", object_color );
}
int totalNum = objDescriptors->total < imageKeypoints->total?
objDescriptors->total:imageKeypoints->total;
double ratio = pow((double)matchNum/totalNum,1.0/9);
if(showInfo)
#ifndef __AFXWIN_H__
cout<<"match : "<<matchNum<<"("<<totalNum<<")"<<endl<<"ratio: "<<ratio<<endl;
#else
sprintf(info,"%smatch : %d\tratio: %g\r\n",info,matchNum,ratio);
#endif
if(showMatch)
{
cvNamedWindow("Object Correspond", 1);
cvShowImage( "Object Correspond", find_obj_match );
}
cvWaitKey(0);
if(showSurf)
cvDestroyWindow("Object");
if(showMatch)
cvDestroyWindow("Object Correspond");
releaseImg(&object_color);
releaseImg(&correspond);
if(showMatch)
releaseImg(&find_obj_match);
cvReleaseMemStorage(&storage);
#ifndef __AFXWIN_H__
cout<<"surf角点匹配率为:\t"<<ratio<<endl;
#else
sprintf(info,"%ssurf角点匹配率为:\t%g\r\n",info,ratio);
#endif
return ratio;
}
double find_obj(cchar* imgName,cchar* objName,int showInfo,int showMatch,int showSurf)
{
#ifndef __AFXWIN_H__
IplImage* object = loadImg( objName, 0,0,0,showInfo );
IplImage* image = loadImg( imgName, 0,0,0,showInfo );
#else
IplImage* object = loadImg( objName, 0,0,0,0 );
IplImage* image = loadImg( imgName, 0,0,0,0 );
#endif
if( !object || !image )