Detection of map contour lines

Detection of map contour lines

This project shows a possible way of finding contour lines on maps. These properties of the contour lines are considered here:

  • contour lines are closed or they end at the edges of the map,
  • in some sections more neighbor contour lines are nearly parallel,
  • they are mainly slightly curved only (the lines do not have large angles like roads or buildings).

The algorithm uses the OpenCV library.

Functions used: cv::medianBlur, cv::Sobel, cv::magnitude

The process

  1. Image preprocessing – using median blur
    cv::Mat bl;
    cv::medianBlur(input, bl, params_.medianBlurKSize);
    
  2. Detecting lines and their directions – using Sobel filter (magnitudes are obtained using the magnitude function and directions are computed using atan2 from horizontal and vertical gradients)
    cv::Mat_<double> grad_x;
    cv::Sobel(beforeSobel, grad_x, CV_64F, 1, 0, params_.sobelKSize);
    cv::Sobel(beforeSobel, grad_y, CV_64F, 0, 1, params_.sobelKSize);
    
  3. Finding some contour line seeds – points at lines with approximately equal directions.
    cv::Mat_<double> magnitude;
    cv::magnitude(grad_x, grad_y, magnitude);
    
  4. Tracing lines beginning at the seeds – we are going from each seed to both directions to find the line while checking if the curves do not exceed a threshold (the more curved lines are probably not the contour lines).
  5. Filtering of the traced lines – only the lines having both ends at the image boundaries or the closed lines are considered as the map contour lines.

Input image.

Finding some contour line seeds.

Result – contour lines detected.

The result image shows a map with some contour lines detected. The seeds and line points are marked as follows:

  • yellow – seed points
  • red – closed line points
  • green – points of the first part of a line ending at the image edge
  • blue – points of the second part of a line ending at the image edge

Problems and possible improvements

These algorithm properties cause problems and need to be considered in the algorithm improvements:

  • line intersections are not being detected – one line from each pair of the intersecting lines should always be removed,
  • the algorithm uses a global magnitude threshold (the threshold determines if a point belongs to a line), but the line intensities change in most images,
  • the algorithm has too many parameters which were not generalized to match more possible images,
  • some contour lines are not continuous (they are splitted by labels) and thus not being detected by the algorithm.