比较两个图像是否相似或一致。（https://pan.baidu.com/s/1htqQ5pi）

cvdiff.cpp

//采用OpenCV轮廓匹配判断两个简单图片是否相似或一致
#include <iostream>
#include <opencv/cv.hpp>

//测试图片B是否与图片A相似，越接近0表示越相似，反之不相似
//IplImage到Mat转换：http://blog.sina.com.cn/s/blog_534497fd01015k7z.html
//参考：http://blog.csdn.net/qq_18343569/article/details/48004201
//参考：http://blog.csdn.net/qq_15947787/article/details/72773893
double TestDifference(const IplImage *imgA, const IplImage *imgB, int method = CV_CONTOURS_MATCH_I1,
	double thresholdA1 = 50, double thresholdA2 = 60, double thresholdB1 = 50, double thresholdB2 = 60)
{
	IplImage* bw_mode = cvCreateImage(cvGetSize(imgA), imgA->depth, 1);
	IplImage* bw_test = cvCreateImage(cvGetSize(imgB), imgA->depth, 1);
	IplImage* canny_mode = cvCreateImage(cvGetSize(imgA), imgA->depth, 1);
	IplImage* canny_test = cvCreateImage(cvGetSize(imgB), imgA->depth, 1);

	CvMemStorage *mode_mems = cvCreateMemStorage();
	CvSeq *mode_seqs;
	CvMemStorage *test_mems = cvCreateMemStorage();
	CvSeq *test_seqs;

	cvCvtColor(imgA, bw_mode, CV_RGB2GRAY);
	cvCvtColor(imgB, bw_test, CV_RGB2GRAY);

	//model contours
	cvCanny(bw_mode, canny_mode, thresholdA1, thresholdA2);
	cvFindContours(canny_mode, mode_mems, &mode_seqs, sizeof(CvContour), CV_RETR_TREE);

	//test contours
	cvCanny(bw_test, canny_test, thresholdB1, thresholdB2);
	cvFindContours(canny_test, test_mems, &test_seqs, sizeof(CvContour), CV_RETR_TREE);

	double desimilarity = cvMatchShapes(test_seqs, mode_seqs, method);

	cvReleaseImage(&bw_mode);
	cvReleaseImage(&bw_test);
	cvReleaseImage(&canny_mode);
	cvReleaseImage(&canny_test);

	return desimilarity;
}

std::string TrimPath(const char *p)
{
	std::string path(p);
	if (path[0] == '"')
		path = path.substr(1, path.size() - 2);
	return path;
}

template<typename T>T TrimNum(const char *p)
{
	std::stringstream ss;
	T d;
	ss << p;
	ss >> d;
	return d;
}

int main(int argc, char *argv[])
{
	double ta1 = 50, ta2 = 60, tb1 = 50, tb2 = 60;
	int m = CV_CONTOURS_MATCH_I1;
	IplImage *imgA, *imgB;
	switch (argc)
	{
	case 8:tb2 = TrimNum<double>(argv[7]);
	case 7:tb1 = TrimNum<double>(argv[6]);
	case 6:ta2 = TrimNum<double>(argv[5]);
	case 5:ta1 = TrimNum<double>(argv[4]);
	case 4:m = TrimNum<int>(argv[3]);
	case 3:
		imgA = cvLoadImage(TrimPath(argv[1]).c_str());
		imgB = cvLoadImage(TrimPath(argv[2]).c_str());
		break;
	default:
		std::cout << "命令行：\n" << argv[0] << " <图A> <图B> [匹配方法(1|2|3)] [阈值A1] [阈值A2] [阈值B1] [阈值B2]\n";
		return 0;
	}
	std::cout << "差异：" << TestDifference(imgA, imgB, m, ta1, ta2, tb1, tb2) << std::endl;
	cvReleaseImage(&imgA);
	cvReleaseImage(&imgB);
	return 0;
}