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How Can OpenCV Be Optimized to Accurately Detect the Four Corners of a Sheet of Paper?
How Can OpenCV Be Optimized to Accurately Detect the Four Corners of a Sheet of Paper?
Dec 24, 2024 am 11:22 AM
Detecting a Sheet of Paper (Square Detection) Using OpenCV
Initial Problem:
A developer successfully implemented the OpenCV square detection example, but the output is cluttered with unnecessary contours. The goal is to filter the results to obtain the four corner points of a sheet of paper for further processing.
Proposed Solution:
The provided code snippet detects squares using multiple threshold levels and eliminates potential holes between edge segments using dilation. However, it does not filter out the clutter. To solve this issue, modify the find_squares function as follows:
void find_squares(Mat& image, vector<vector<Point> >& squares)
{
... [code as before] ...
// Filter out unnecessary contours and store the largest square
vector<Point> largestSquare;
double maxArea = 0;
for (auto& square : squares)
{
double area = fabs(contourArea(Mat(square)));
if (area > maxArea)
{
maxArea = area;
largestSquare = square;
}
}
squares.clear(); // Clear existing squares vector
squares.push_back(largestSquare); // Store the largest square
}
Final Output:
After applying this modification, the resulting vector squares will contain only the four corner points of the detected sheet of paper as the largest square in the image. This can then be used forskew reduction or further image processing tasks.
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