我想通过简单的模板匹配来进行图像识别。

把预处理好的字符图片，分别与A到Z的样本图片进行模板匹配。

结果最大的表明相关性最大，就能够识别字符图片了。

在实际应用中。我用了openCV的matchTemplate()函数，可是未达到我想要点的效果。

matchTemplate()的功能是在图像中搜索出指定的模板，假设模板是从待搜索的图像中截取出来的，会有非常好的效果。可是假设模板不是待搜素图像的一部分，似乎达不到我想要的效果。

在尝试了matlab的corr2()后。发现corr2能非常好的解决我的问题。

double Card::corr2(Mat matA, Mat matB){

	//计算两个同样大小矩阵的二维相关系数

	double corr2 = 0;

	double Amean2 = 0;

	double Bmean2 = 0;

	for (int m = 0; m < matA.rows; m++) {

		uchar* dataA = matA.ptr<uchar>(m);

		uchar* dataB = matB.ptr<uchar>(m);

		for (int n = 0; n < matA.cols;n++) {

			Amean2 = Amean2 + dataA[n];

			Bmean2 = Bmean2 + dataB[n];

		}

	}

	Amean2 = Amean2 / (matA.rows * matA.cols);

	Bmean2 = Bmean2 / (matB.rows * matB.cols);

	double Cov = 0;

	double Astd = 0;

	double Bstd = 0;

	for (int m = 0; m < matA.rows; m++) {

		uchar* dataA = matA.ptr<uchar>(m);

		uchar* dataB = matB.ptr<uchar>(m);

		for (int n = 0; n < matA.cols;n++) {

			//协方差

			Cov = Cov + (dataA[n] - Amean2) * (dataB[n] - Bmean2);

			//A的方差

			Astd = Astd + (dataA[n] - Amean2) * (dataA[n] - Amean2);

			//B的方差

			Bstd = Bstd + (dataB[n] - Bmean2) * (dataB[n] - Bmean2);

		}

	}

	corr2 = Cov / (sqrt(Astd * Bstd));

	return corr2;

}

//待搜索图像

Mat srcImage = imread("M:/图像处理实验/验证码/byx001.bmp",1);

Mat resizeMat = Mat::zeros(25, 25, CV_8UC3);

//缩放为25*25的矩阵。由于要相关匹配的模板大小为25*25

resize(srcImage,resizeMat,resizeMat.size());

//相关匹配

double ccorrVal[26] = {0};

double max = 0;

int count = 0;

for (int m = 0; m < 26; m++){

	char recogPath[100] = {1};

	strcpy(recogPath,"M://图像处理实验//验证码//大写字母//");

	char num[2] = {1};

	num[0] = 65 + m;

	strcat(recogPath, num);

	strcat(recogPath,".bmp");

	Mat img_display;

	resizeMat.copyTo( img_display );

	Mat std = imread(recogPath,0);

	Mat resizeMatSTD = Mat::zeros(25, 25, CV_8UC3);

	resize(std,resizeMatSTD,resizeMatSTD.size());

	adaptiveThreshold(resizeMatSTD ,resizeMatSTD ,255 ,ADAPTIVE_THRESH_MEAN_C ,THRESH_BINARY,5,1);

	corr2Val[m] = corr2(resizeMatSTD,img_display);

	if (max <= corr2Val[m]){

		max = corr2Val[m];

		count = m;

	}

}

char pathname[100]={1};

strcpy(pathname,"M://图像处理实验//验证码//test//字符_");

char num[10];

_itoa(i, num, 10);

strcat(pathname, num);

char C[2] = {1};

C[0] = 65 + count;

strcat(pathname, C);

strcat(pathname,".bmp");

imwrite(pathname, resizeMat);

字符模板：

识别结果输出：