Evaluation of Roof Edge Detectors with a Quantitative Error Measure
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.
Cite As
Baptiste Magnier (2024). Evaluation of Roof Edge Detectors with a Quantitative Error Measure (https://www.mathworks.com/matlabcentral/fileexchange/58415-evaluation-of-roof-edge-detectors-with-a-quantitative-error-measure), MATLAB Central File Exchange. Retrieved .
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- Image Processing and Computer Vision > Image Processing Toolbox > Image Segmentation and Analysis > Object Analysis >
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