This OpenCV C++ Tutorial is about Slant Line Detection i.e. detecting lines inclined at minus 45 degrees
To detect slant lines inclined at -45 degress, we use the mask:
Thus sliding this mask over an Image we can detect Lines inclined at -45 degrees.
Here is the Opencv C++ Example of Slant Line (lines/edges at 45 degrees)Detection below:
Here is the Opencv C++ Example of Slant Line (lines/edges at 45 degrees)Detection below:
Input:
Output:
To detect slant lines inclined at -45 degress, we use the mask:
2 | -1 | -1 |
-1 | 2 | -1 |
-1 | -1 | 2 |
Thus sliding this mask over an Image we can detect Lines inclined at -45 degrees.
Here is the Opencv C++ Example of Slant Line (lines/edges at 45 degrees)Detection below:
Here is the Opencv C++ Example of Slant Line (lines/edges at 45 degrees)Detection below:
//Opencv C++ Code for detecting line inclined at minus 45 degree #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include "iostream" using namespace cv; using namespace std; int main( ) { Mat src1,src2; int a; Scalar intensity1=0; src1 = imread("C:\\Users\\arjun\\Desktop\\opencv-test.jpg", CV_LOAD_IMAGE_GRAYSCALE); src2 = src1.clone(); //If image not found if (!src1.data) { cout << "No image data \n"; return -1; } //Take the Size of Mask cout<<"Enter the mask Size ="; cin>>a; //for loop for counting the number of rows and columns and displaying the pixel value at each point for (int i = 0; i < src1.rows-a; i++) { for (int j = 0; j < src1.cols-a; j++) { Scalar intensity2=0; for (int p = 0; p<a; p++) { for (int q = 0; q<a; q++) { intensity1 = src1.at<uchar>(i+p,j+q); if (p==q) { intensity2.val[0] +=(a-1)*intensity1.val[0]; } else { intensity2.val[0] +=(-1)*intensity1.val[0]; } } } src2.at<uchar>(i+(a-1)/2,j+(a-1)/2)=intensity2.val[0]/(a*a); } } //Display the original image namedWindow("Display Image"); imshow("Display Image", src1); //Display the Low Pass Filtered Image image namedWindow("Low Pass Filtered Image"); imshow("Low Pass Filtered Image", src2); imwrite("C:\\Users\\arjun\\Desktop\\opencv-slant-line.jpg",src2); waitKey(0); return 0; }
Input:
Output:
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