Evaluation of Roof Edge Detectors with a Quantitative Error Measure

Perform a KPI (Key Performance Indicator) computation for an edge detection

This work evaluates a crest line detection.
Comparing the ground truth contour image and the candidate crest line image, the proposed algorithm is based upon a new criterion (KPI) that take into account the list of ground truth, the recall and their associated spacial nearness.
Doubtlessly, an efficient evaluation penalizes a misplaced edge point proportionally to the distance to the true contour.
For a given experiment, a KPI value close to 1 means a poor segmentation.
Alternatively, a KPI value close to 0 translates a good segmentation (i.e. good image candidate of edges).
Eventually, image tests are proposed in the .zip file.