图像水平投影和垂直投影，图像分割

图像水平投影和垂直投影，图像分割

// opencv.cpp : 此文件包含 "main" 函数。程序执行将在此处开始并结束。
//
//#pragma comment(lib , "D:/OpenCV4.5.1/opencv/build/x64/vc15/lib/opencv_world451d.lib")
//#pragma comment(lib , "D:/OpenCV4.5.1/opencv/newbuild_64/install/x64/vc15/lib/opencv_world451d.lib")
#include 
#include 
#include 
#include 
#include 

#include 
#include 
#include 
#include 
#include 



using namespace cv;
using namespace std;
using namespace ml;




//积分二值化
void thresholdIntegral(Mat inputMat, Mat& outputMat)
{

	int nRows = inputMat.rows;
	int nCols = inputMat.cols;

	// 创建积分图
	Mat sumMat;
	integral(inputMat, sumMat);

	//把图分成8份 （n份)
	int S = MAX(nRows, nCols) / 8;
	double T = 0.15;

	//
	int s2 = S / 2;
	int x1, y1, x2, y2, count, sum;

	int* p_y1, *p_y2;
	uchar* p_inputMat, *p_outputMat;

	for (int i = 0; i < nRows; ++i)
	{
		//找行的范围
		y1 = i - s2;
		y2 = i + s2;

		if (y1 < 0)
		{
			y1 = 0;
		}
		if (y2 >= nRows)
		{
			y2 = nRows - 1;
		}

		//取出区域行的左上角和左下角
		p_y1 = sumMat.ptr<int>(y1);
		p_y2 = sumMat.ptr<int>(y2);
		//取出图像某行的像素值
		p_inputMat = inputMat.ptr<uchar>(i);
		p_outputMat = outputMat.ptr<uchar>(i);

		for (int j = 0; j < nCols; ++j)
		{
			//找列的范围
			// 设置 SxS 区域
			x1 = j - s2;
			x2 = j + s2;

			if (x1 < 0)
			{
				x1 = 0;
			}
			if (x2 >= nCols)
			{
				x2 = nCols - 1;
			}

			//区域内像素的个数
			count = (x2 - x1)* (y2 - y1);

			//获取区域内像素个数的 累加的像素值
			// I(x,y)=s(x2,y2)-s(x1,y2)-s(x2,y1)+s(x1,x1)
			sum = p_y2[x2] - p_y1[x2] - p_y2[x1] + p_y1[x1];

			//如果图像的当前像素值低于区域内的平均像素值(加权：在这里是0.85)  设为0
			if ((int)(p_inputMat[j] * count) < (int)(sum* (1.0 - T)))
			{
				p_outputMat[j] = 0;
			}
			else
			{
				p_outputMat[j] = 255;
			}
		}
	}
}
//垂直方向投影
void picshadowx(Mat binary, vector<Mat> &result)
{
	Mat paintx(binary.size(), CV_8UC1, Scalar(255)); //创建一个全白图片，用作显示

	int* blackcout = new int[binary.cols];
	memset(blackcout, 0, binary.cols * 4);

	for (int i = 0; i < binary.rows; i++)
	{
		for (int j = 0; j < binary.cols; j++)
		{
			if (binary.at<uchar>(i, j) == 0)
			{
				blackcout[j]++; //垂直投影按列在x轴进行投影
			}
		}
	}
	for (int i = 0; i < binary.cols; i++)
	{
		for (int j = 0; j < blackcout[i]; j++)
		{
			paintx.at<uchar>(binary.rows - 1 - j, i) = 0; //翻转到下面，便于观看
		}
	}
	imshow("paintx", paintx);


	int startindex = 0;
	int endindex = 0;
	bool inblock = false; //是否遍历到字符位置

	for (int i = 0; i < paintx.cols; i++)
	{

		if (!inblock&&blackcout[i] != 0) //进入有字符区域
		{
			inblock = true;
			startindex = i;
			cout << "startindex:" << startindex << endl;
		}
		if (inblock&&blackcout[i] == 0) //进入空白区
		{
			endindex = i;
			inblock = false;
			Mat roi = binary.colRange(startindex, endindex + 1); //从而记录从开始到结束列的位置，即可进行行切分
			result.push_back(roi);
		}
	}

	delete blackcout;
	

}
//水平方向投影并行分割
void picshadowy(Mat binary,vector<Mat> &result)
{
	//是否为白色或者黑色根据二值图像的处理得来
	Mat painty(binary.size(), CV_8UC1, Scalar(255)); //初始化为全白

   //水平投影
	int* pointcount = new int[binary.rows]; //在二值图片中记录行中特征点的个数
	memset(pointcount, 0, binary.rows * 4);//注意这里需要进行初始化

	for (int i = 0; i < binary.rows; i++)
	{
		for (int j = 0; j < binary.cols; j++)
		{
			if (binary.at<uchar>(i, j) == 0)
			{
				pointcount[i]++; //记录每行中黑色点的个数 //水平投影按行在y轴上的投影
			}
		}
	}

	for (int i = 0; i < binary.rows; i++)
	{
		for (int j = 0; j < pointcount[i]; j++) //根据每行中黑色点的个数，进行循环
		{
			painty.at<uchar>(i, j) = 0;
		}
	}

	imshow("painty", painty);

	int startindex = 0;
	int endindex = 0;
	bool inblock = false; //是否遍历到字符位置

	for (int i = 0; i < painty.rows; i++)
	{

		if (!inblock&&pointcount[i] != 0) //进入有字符区域
		{
			inblock = true;
			startindex = i;
			cout << "startindex:" << startindex << endl;
		}
		if (inblock&&pointcount[i] == 0) //进入空白区
		{
			endindex = i;
			inblock = false;
			Mat roi = binary.rowRange(startindex, endindex + 1); //从而记录从开始到结束行的位置，即可进行行切分
			result.push_back(roi);
		}
	}

	delete pointcount;

}
int main(int argc, char* argv[])
{

	Mat src = cv::imread("test_number.jpg");

	if (src.empty())
	{
		cerr << "Problem loading image!!!" << endl;
		return -1;
	}

	imshow("in", src);

	Mat gray;

	if (src.channels() == 3)
	{
		cv::cvtColor(src, gray,COLOR_BGR2GRAY);
	}
	else
	{
		gray = src;
	}


	Mat bw2 = Mat::zeros(gray.size(), CV_8UC1);
	thresholdIntegral(gray, bw2);

	cv::imshow("binary integral", bw2);

	vector<Mat> result;

	picshadowy(bw2, result);
	for (int i = 0; i < result.size(); i++)
	{
		vector<Mat> result1;
		picshadowx(result[i], result1);

		for (int j = 0; j < result1.size(); j++)
		{
			Mat tmp = result1[j];
			imshow("test" + to_string(i) + to_string(j), tmp);
		}
	}
	

	waitKey(0);

	return 0;
}