opencv学习笔记2——surf算法demo中find_obj分析

main函数分析

int main(int argc, char** argv)
{
//物体和背景图片名
const char* object_filename = argc == 3 ? argv[1] : "D:/OpenCV2.1/samples/c/box.png";
const char* scene_filename = argc == 3 ? argv[2] : "C:/11.bmp";


CvMemStorage* storage = cvCreateMemStorage(0);


//显示物体窗口
cvNamedWindow("Object", 1);
cvNamedWindow("Object Correspond", 1);


//调色板
static CvScalar colors[] = 
{
{{0,0,255}},
{{0,128,255}},
{{0,255,255}},
{{0,255,0}},
{{255,128,0}},
{{255,255,0}},
{{255,0,0}},
{{255,0,255}},
{{255,255,255}}
};


//载入物体和背景的图片
IplImage* object = cvLoadImage( object_filename, CV_LOAD_IMAGE_GRAYSCALE );
IplImage* image = cvLoadImage( scene_filename, CV_LOAD_IMAGE_GRAYSCALE );
if( !object || !image )
{
fprintf( stderr, "Can not load %s and/or %s\n"
"Usage: find_obj [<object_filename> <scene_filename>]\n",
object_filename, scene_filename );
exit(-1);
}


//将物体图片的颜色转换
IplImage* object_color = cvCreateImage(cvGetSize(object), 8, 3);
cvCvtColor( object, object_color, CV_GRAY2BGR );


//分别定义物体和图片特征点变量
CvSeq *objectKeypoints = 0, *objectDescriptors = 0;
CvSeq *imageKeypoints = 0, *imageDescriptors = 0;


//检测前设置，设hessianThreshold值为500
int i;
CvSURFParams params = cvSURFParams(500, 1);


//提取物体surf特征点
cvExtractSURF( object, 0, &objectKeypoints, &objectDescriptors, storage, params );
printf("Object Descriptors: %d\n", objectDescriptors->total);
//提取图片特征点
cvExtractSURF( image, 0, &imageKeypoints, &imageDescriptors, storage, params );
printf("Image Descriptors: %d\n", imageDescriptors->total);


//计算提取时间
double tt = (double)cvGetTickCount();
tt = (double)cvGetTickCount() - tt;
printf( "Extraction time = %gms\n", tt/(cvGetTickFrequency()*1000.));


//源物体图片的四个顶点
CvPoint src_corners[4] = {{0,0}, {object->width,0}, {object->width, object->height}, {0, object->height}};


//CvPoint dst_corners[4];


//？？？与背景图片大小一致
IplImage* correspond = cvCreateImage( cvSize(image->width, object->height+image->height), 8, 1 );

//设置图片中感兴趣的区域
cvSetImageROI( correspond, cvRect( 0, 0, object->width, object->height ) );
cvCopy( object, correspond );
cvSetImageROI( correspond, cvRect( 0, object->height, correspond->width, correspond->height ) );
cvCopy( image, correspond );
cvResetImageROI( correspond );
/*
#ifdef USE_FLANN
printf("Using approximate nearest neighbor search\n");
#endif
*/


//如果找到物体的位置，则用线和点标出
if( locatePlanarObject( objectKeypoints, objectDescriptors, imageKeypoints,
imageDescriptors, src_corners, dst_corners ))
{
for( i = 0; i < 4; i++ )
{
CvPoint r1 = dst_corners[i%4];
CvPoint r2 = dst_corners[(i+1)%4];
cvLine( correspond, cvPoint(r1.x, r1.y+object->height ),
cvPoint(r2.x, r2.y+object->height ), colors[8] );
}
}


//定义匹配对
vector<int> ptpairs;
/*
#ifdef USE_FLANN
flannFindPairs( objectKeypoints, objectDescriptors, imageKeypoints, imageDescriptors, ptpairs );
#else
findPairs( objectKeypoints, objectDescriptors, imageKeypoints, imageDescriptors, ptpairs );
#endif
*/  
//找到匹配对，标出
findPairs( objectKeypoints, objectDescriptors, imageKeypoints, imageDescriptors, ptpairs );
for( i = 0; i < (int)ptpairs.size(); i += 2 )
{
CvSURFPoint* r1 = (CvSURFPoint*)cvGetSeqElem( objectKeypoints, ptpairs[i] );
CvSURFPoint* r2 = (CvSURFPoint*)cvGetSeqElem( imageKeypoints, ptpairs[i+1] );
cvLine( correspond, cvPointFrom32f(r1->pt),
cvPoint(cvRound(r2->pt.x), cvRound(r2->pt.y+object->height)), colors[8] );
}


//画出图片中的物体位置
cvShowImage( "Object Correspond", correspond );
for( i = 0; i < objectKeypoints->total; i++ )
{
CvSURFPoint* r = (CvSURFPoint*)cvGetSeqElem( objectKeypoints, i );
CvPoint center;
int radius;
center.x = cvRound(r->pt.x);
center.y = cvRound(r->pt.y);
radius = cvRound(r->size*1.2/9.*2);
cvCircle( object_color, center, radius, colors[0], 1, 8, 0 );
}
cvShowImage( "Object", object_color );


cvWaitKey(0);


cvDestroyWindow("Object");
cvDestroyWindow("Object SURF");
cvDestroyWindow("Object Correspond");


return 0;
}