match.c

opencv下的图像sift特征提取以及匹配

/*
Detects SIFT features in two images and finds matches between them.

Copyright (C) 2006  Rob Hess <[e-mail]>

@version 1.1.1-20070330

*/

//---OpenCV的库文件-----------
#pragma comment (lib,"cv")
#pragma comment (lib,"highgui")
#pragma comment (lib, "cxcore")

//---gsl的库文件-----------
#pragma comment (lib, "libgsl.a")



#include "sift.h"
#include "imgfeatures.h"
#include "kdtree.h"
#include "utils.h"
#include "xform.h"

#include <cv.h>
#include <cxcore.h>
#include <highgui.h>

#include <stdio.h>

#include <iostream.h>

/* the maximum number of keypoint NN candidates to check during BBF search */
#define KDTREE_BBF_MAX_NN_CHKS 200

/* threshold on squared ratio of distances between NN and 2nd NN */
#define NN_SQ_DIST_RATIO_THR 0.49

/******************************** Globals ************************************/

char img1_file[] = ".\\beaver.png";		//怎么VC下一个点就够了的 .net下需要两个点
char img2_file[] = ".\\beaver_xform.png";

//char img1_file[] = ".\\034.JPG";		//怎么VC下一个点就够了的 .net下需要两个点
//char img2_file[] = ".\\035.JPG";



double imgzoom_scale=1.0;			//显示匹配结果图的缩放比例

			

IplImage* stacked;


/**************************other functions **************************************/


//----鼠标响应函数（用于根据鼠键响应缩放匹配结果的窗口大小）
void on_mouse( int event, int x, int y, int flags, void* param ) ;

//---改变匹配结果图像的大小------------------------

void resize_img();

/********************************** Main *************************************/


int main( int argc, char** argv )
{

	IplImage* img1, * img2;

	struct feature* feat1, * feat2, * feat;
	struct feature** nbrs;
	struct kd_node* kd_root;
	CvPoint pt1, pt2;
	double d0, d1;
	int n1, n2, k, i, m = 0;

	//------------内存存储器------------
	CvMemStorage* memstorage = cvCreateMemStorage(0);

	//-----------up_seq存储img1匹配出的特征点的坐标-----------

	CvSeq *up_seq = cvCreateSeq(	CV_SEQ_ELTYPE_POINT,
					sizeof(CvSeq),
					sizeof(CvPoint),
					memstorage); 

	//-----------down_seq存储img2匹配出的特征点的坐标-----------

	CvSeq *down_seq = cvCreateSeq(	CV_SEQ_ELTYPE_POINT,
					sizeof(CvSeq),
					sizeof(CvPoint),
					memstorage); 


	img1 = cvLoadImage( img1_file, 1 );
	if( ! img1 )
		fatal_error( "unable to load image from %s", img1_file );
	img2 = cvLoadImage( img2_file, 1 );
	if( ! img2 )
		fatal_error( "unable to load image from %s", img2_file );

	stacked = stack_imgs( img1, img2 );


	fprintf( stderr, "Finding features in %s...\n", img1_file );
	n1 = sift_features( img1, &feat1 );

	

	fprintf( stderr, "Finding features in %s...\n", img2_file );
	n2 = sift_features( img2, &feat2 );


	//----------显示img1的SIFT特征---------
	if(1)
	{
		draw_features( img1, feat1, n1 );
		cvNamedWindow( "img1_feature", 1 );
		cvShowImage( "img1_feature", img1 );

	}


	//----------显示img2的SIFT特征---------
	if(1)
	{
		draw_features( img2, feat2, n2 );
		cvNamedWindow( "img2_feature", 1 );
		cvShowImage( "img2_feature", img2 );
	}



	kd_root = kdtree_build( feat2, n2 );

	for( i = 0; i < n1; i++ )
	{
		feat = feat1 + i;
		k = kdtree_bbf_knn( kd_root, feat, 2, &nbrs, KDTREE_BBF_MAX_NN_CHKS );
		if( k == 2 )
		{
			d0 = descr_dist_sq( feat, nbrs[0] );
			d1 = descr_dist_sq( feat, nbrs[1] );
			if( d0 < d1 * NN_SQ_DIST_RATIO_THR )
			{
				pt1 = cvPoint( cvRound( feat->x ), cvRound( feat->y ) );
				pt2 = cvPoint( cvRound( nbrs[0]->x ), cvRound( nbrs[0]->y ) );

				//---------存储单个点坐标到点序列中----------
				cvSeqPush(up_seq,&pt1); 
				cvSeqPush(down_seq,&pt2);


				pt2.y += img1->height;
				cvLine( stacked, pt1, pt2, CV_RGB(255,0,255), 1, 8, 0 );
				m++;
				feat1[i].fwd_match = nbrs[0];

				
			}
		}
		free( nbrs );
	}




	fprintf( stderr, "Found %d total matches\n", m );



	//---------存储匹配点的坐标到文件-----------------

	cvSave("upimg_matched_points.xml", up_seq, NULL, "matched_points_up", cvAttrList(NULL,NULL));
	cvSave("downimg_matched_points.xml", down_seq, NULL, "matched_points_down", cvAttrList(NULL,NULL));

	fprintf( stderr, "%d 个匹配的点的坐标已分别保存到文件:\n upimg_matched_points.xml和downimg_matched_points.xml\n", m );		

	resize_img();

	cvWaitKey( 0 );


	/* 
	UNCOMMENT BELOW TO SEE HOW RANSAC FUNCTION WORKS

	Note that this line above:

	feat1[i].fwd_match = nbrs[0];

	is important for the RANSAC function to work.
	*/
	/*
	{
		CvMat* H;
		H = ransac_xform( feat1, n1, FEATURE_FWD_MATCH, lsq_homog, 4, 0.01,
			homog_xfer_err, 3.0, NULL, NULL );
		if( H )
		{
			IplImage* xformed;
			xformed = cvCreateImage( cvGetSize( img2 ), IPL_DEPTH_8U, 3 );
			cvWarpPerspective( img1, xformed, H, 
				CV_INTER_LINEAR + CV_WARP_FILL_OUTLIERS,
				cvScalarAll( 0 ) );
			cvNamedWindow( "Xformed", 1 );
			cvShowImage( "Xformed", xformed );
			cvWaitKey( 0 );
			cvReleaseImage( &xformed );
			cvReleaseMat( &H );
		}
	}
	*/

	//------释放内存存储器-----------
	cvReleaseMemStorage( &memstorage );
	cvReleaseImage( &stacked );
	cvReleaseImage( &img1 );
	cvReleaseImage( &img2 );
	kdtree_release( kd_root );
	free( feat1 );
	free( feat2 );
	return 0;
}



void on_mouse( int event, int x, int y, int flags, void* param ) 
{
	if( (event==CV_EVENT_LBUTTONUP) &&  (flags==CV_EVENT_FLAG_CTRLKEY) ) 
	{
				
	}
	
	
	
	if( (event==CV_EVENT_LBUTTONUP) &&  (flags==CV_EVENT_FLAG_ALTKEY) ) 
		//ALT和鼠标左键开始按下的时候放大匹配结果图
	{
		
		
		//---------特征点匹配函数--------------	
		if(imgzoom_scale<1.5)
		{
			imgzoom_scale=1.1*imgzoom_scale;
		}
		
		else imgzoom_scale=1.0;
		//----放大匹配结果图-----
		resize_img();

	}
	
	if( (event==CV_EVENT_RBUTTONUP) &&  (flags==CV_EVENT_FLAG_ALTKEY) ) 
		
		//ALT和鼠标右键开始按下的时候缩小匹配结果图
	{
		
		
		//---------特征点匹配函数--------------	
		if(imgzoom_scale>0.0)
		{
			imgzoom_scale=0.9*imgzoom_scale;
		}
		
		else imgzoom_scale=0.5;

		//----缩小匹配结果图-----
		resize_img();

		//printf("%f\n",imgzoom_scale);

	}
	

}



//--------------改变匹配结果图像的大小------------------------

void resize_img()
{
	IplImage* resize_stacked;

	resize_stacked=cvCreateImage(cvSize(  (int)(stacked->width*imgzoom_scale),  (int)(stacked->height*imgzoom_scale)  ),
				stacked->depth,
				stacked->nChannels);
	//----缩放匹配结果图的大小------

	cvResize(stacked, resize_stacked, CV_INTER_AREA );
	
	printf("\n同时ALT键和鼠标右键按下将缩小匹配结果图\n\n");

	printf("同时ALT键和鼠标左键按下将放大匹配结果图\n");


	cvNamedWindow( "Matches", 1 );

	
	//---------鼠键响应函数--------------
	
	cvSetMouseCallback("Matches", on_mouse, 0 );
	

	cvShowImage( "Matches", resize_stacked);

	cvWaitKey( 0 );




}