OpenCV 实现图片的水平投影与垂直投影，并进行行分割

对于印刷体图片来说，进行水平投影和垂直投影可以很快的进行分割，本文就在OpenCV中如何进行水平投影和垂直投影通过代码进行说明。

水平投影：二维图像在y轴上的投影

垂直投影：二维图像在x轴上的投影

由于投影的图像需要进行二值化，本文采用积分二值化的方式，对图片进行处理。

具体代码如下：

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

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

// create the integral image
Mat sumMat;
integral (inputMat, sumMat);

int S = MAX (nRows, nCols) / 8;
double T = 0.15;

// perform thresholding
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)
{
y1 = i - s2;
y2 = i + s2;

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

p_y1 = sumMat.ptr<int> (y1);
p_y2 = sumMat.ptr<int> (y2);
p_inputMat = inputMat.ptr<uchar> (i);
p_outputMat = outputMat.ptr<uchar> (i);

for (int j = 0; j < nCols; ++j)
{
// set the SxS region
x1 = j - s2;
x2 = j + s2;

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

count = (x2 - x1)* (y2 - y1);

// 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];

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)
{
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
}
}
delete blackcout;
imshow ("paintx", paintx);

}
//水平方向投影并行分割
void picshadowy (Mat binary)
{
//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);

vector<Mat> result;
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);
}
}

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

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

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

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

imshow("in",src);

Mat gray;

if (src.channels() == 3)
{
cv::cvtColor (src, gray, CV_BGR2GRAY);
}
else
{
gray = src;
}

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

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

//picshadowx (bw2);
picshadowy (bw2);
waitKey (0);

return 0;
}

输入图片：

OpenCV 实现图片的水平投影与垂直投影，并进行行分割