@InProceedings{8081564,
  author = {V. Baltazart and L. Yang and P. Nicolle and J. Moliard},
  booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},
  title = {Pseudo-ground truth data collection on pavement images},
  year = {2017},
  pages = {2021-2025},
  abstract = {The performance assessment of automatic crack detection algorithms within pavement images requires beforehand to establish a reference image, namely, the pseudo-ground truth image (PGT). In this context, this paper presents some existing pseudo-ground truth (PGT) data collection techniques which rely on image processing techniques. The processing of five Single Pair Shortest Path (SPSP) algorithms which are devoted to this aim are illustrated in terms of running time and segmentation accuracy on a pavement image.},
  keywords = {crack detection;data acquisition;image segmentation;roads;structural engineering computing;performance assessment;pseudoground truth data collection techniques;pavement image segmentation;Single Pair Shortest Path algorithms;image processing techniques;PGT;pseudoground truth image;reference image;automatic crack detection algorithms;Signal processing algorithms;Image segmentation;Data collection;Detection algorithms;Europe;Signal processing;Road surface monitoring;crack detection;image processing;Single Pair Shortest Path;DICE similarity coefficient;performance assessment;pseudo-ground truth},
  doi = {10.23919/EUSIPCO.2017.8081564},
  issn = {2076-1465},
  month = {Aug},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570347183.pdf},
}

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