这是我与RLSA in C++相关的旧问题,但我还没有得到任何帮助。
我尝试将代码从Matlab实现到C ++
此算法的说明:
http://crblpocr.blogspot.fr/2007/06/run-length-smoothing-algorithm-rlsa.html http://crblpocr.blogspot.fr/2007/06/determination-of-run-length-smoothing.html
这个帖子在Matlab中有RLSA实现:
http://mathworks.cn/matlabcentral/newsreader/view_thread/318198
MatLabCode
hor_thresh=20;
zeros_count=0;
one_flag=0;
hor_image=image;
for i=1:m
for j=1:n
if(image(i,j)==1)
if(one_flag==1)
if(zeros_count<=hor_thresh)
hor_image(i,j-zeros_count:j-1)=1;
else
one_flag=0;
end
zeros_count=0;
end
one_flag=1;
else
if(one_flag==1)
zeros_count=zeros_count+1;
end
end
end
end
我尝试在C ++代码中实现
int hor_thres = 22;
int one_count = 0;
int zero_flag = 0;
Mat tmpImg = Mat(Img.size(), CV_8UC1, Scalar(0, 0, 0));
for (int j = 0; j<Img.rows; j++){
for (int i = 0; i<Img.cols; j++){
if (Img.at<uchar>(j, i) == 0)
{
if (zero_flag == 1)
{
if (one_count <= hor_thres)
{
tmpText(cv::Range(j - zero_count, j), cv::Range(i, i+1)).setTo(cv::Scalar::all(255));
// I want to do the same thing in Matlab as this image(i,j-one_count:j-1)=0;
}
else
{
zero_flag = 1;
}
one_count = 0;
}
zero_flag = 1;
}
else
{
if (zero_flag == 1)
{
one_count = one_count + 1;
}
}
}
}
这次没有错误但结果不合预期..
问题在于我想要编写与
相同的c ++代码Matlab的
tmpImg(i,j-one_count:j-1)=0;
C ++
tmpText(cv::Range(j - zero_count, j), cv::Range(i, i+1)).setTo(cv::Scalar::all(255));
Anyidea ???
另一件事是在Matlab中,索引从1开始,而C ++从0开始。
感谢
答案 0 :(得分:2)
OpenCV按行/列索引,而不是x / y,所以请改为:
if (tmpText.at<uchar>(j, i) == 0)
^^^^
您还需要修复使用at<T>(row,col)
功能的其余代码。
答案 1 :(得分:1)
int hor_thres = 22;
int zero_count = 0;
int one_flag = 0;
for (int i = 0; i<tmpImg.rows; i++){
for (int j = 0; j<tmpImg.cols; j++){
if (tmpImg.at<uchar>(i, j) == 255)
{
if (one_flag == 255)
{
if (zero_count <= hor_thres)
{
tmpImg(cv::Range(i, i + 1), cv::Range(j - zero_count, j)).setTo(cv::Scalar::all(255));
}
else
{
one_flag = 0;
}
zero_count = 0;
}
one_flag = 255;
}
else
{
if (one_flag == 255)
{
zero_count = zero_count + 1;
}
}
}
}
未来的建议是在不使用循环的情况下改进此实现。
答案 2 :(得分:1)
如果你有黑色前景和白色背景,那么希望你会发现我的实现很有用。
Horisontal RLSA
void horizontalRLSA(Mat &input, Mat &output, int thresh)
{
for (int j = 0; j < input.rows; j++)
{
int count = 0;
int flag = 0;
for (int i = 0; i < input.cols; i++)
{
if (input.at<uchar>(j, i) == 255)
{
flag = 255;
count++;
}
else
{
if (flag == 255 && count <= thresh)
{
output(Rect(i - count, j, count, 1)).setTo(Scalar::all(0));
}
flag = 0;
count = 0;
}
}
}
}
垂直RLSA
void verticalRLSA(Mat &input, Mat &output, int thresh)
{
for (int i = 0; i < input.cols; i++)
{
int count = 0;
int flag = 0;
for (int j = 0; j < input.rows; j++)
{
if (input.at<uchar>(j, i) == 255)
{
flag = 255;
count++;
}
else
{
if (flag == 255 && count <= thresh)
{
output(Rect(i, j - count, 1, count)).setTo(Scalar::all(0));
}
flag = 0;
count = 0;
}
}
}
}
<强>用法强>
Mat input_binary_image;
Mat hrlsa = input_binary_image.clone();
horizontalRLSA(input_binary_image, hrlsa, 50);