opencv 中模板匹配的完整例子

Mat object = imread( "chicky_512.png", CV_LOAD_IMAGE_GRAYSCALE );
Mat img_1 = imread( "chicky_512.png", CV_LOAD_IMAGE_GRAYSCALE );
Mat img_2 = imread( "chicky_c.png", CV_LOAD_IMAGE_GRAYSCALE );
if( !object.data )
{
std::cout<< "Error reading object " << std::endl;
return -1;
}
if( !img_1.data || !img_2.data )
{ return -1; }
 //-- Step 1: Detect the keypoints using SURF Detector
//Detect the keypoints using SURF Detector
int minHessian = 500;
/*1 FeatureDetector
FeatureDetector是关键点检测类的抽象基类，其已经实现的具体类有：
class FastFeatureDetector
class GoodFeaturesToTrackDetector
class MserFeatureDetector
class StarFeatureDetector
class SiftFeatureDetector
class SurfFeatureDetector
要使用某一种检测器，可以直接调用FeatureDetector的工厂来创建，该工厂是一个静态方法，如下：
// Create feature detector by detector name.
static Ptr<FeatureDetector> create( const string& detectorType );
也可以像我的示例代码中那样显式的创建，如下：
FeatureDetector *pDetector = new SurfFeatureDetector;
可以用swich实现在多种方法中切换。*/
SurfFeatureDetector detector( minHessian );// 这里我们用了SURF特征点
std::vector<KeyPoint> kp_object;

detector.detect( object, kp_object );

FeatureDetector *pDetector = new SurfFeatureDetector; // 这里我们用了SURF特征点
std::vector<KeyPoint> keypoints_1, keypoints_2;
pDetector->detect(img_1, keypoints_1);
pDetector->detect(img_2, keypoints_2);
delete pDetector;

/*2 DescriptorExtractor
DescriptorExtractor是提取关键点的描述向量类抽象基类，其具体类有：
class SiftDescriptorExtractor
class SurfDescriptorExtractor
class CalonderDescriptorExtractor
class BriefDescriptorExtractor
class OpponentColorDescriptorExtractor
要使用某一种描述向量，可以调用DescriptorExtractor的工厂来创建，静态方法如下：
static Ptr<DescriptorExtractor> create( const string& descriptorExtractorType );
也可以像我的示例代码中那样显式的创建，如下：
DescriptorExtractor *pExtractor = new SurfDescriptorExtractor;
可以用swich实现在多种方法中切换。*/
//Calculate descriptors (feature vectors)
////-- Step 2: Calculate descriptors (feature vectors)// 提取SURF描述向量
SurfDescriptorExtractor extractor;
Mat des_object;
extractor.compute( object, kp_object, des_object );
///////////////////////////
DescriptorExtractor *pExtractor = new SurfDescriptorExtractor; // 提取SURF描述向量
Mat descriptors_1, descriptors_2;
pExtractor->compute(img_1, keypoints_1, descriptors_1);
pExtractor->compute(img_2, keypoints_2, descriptors_2);