ImageSegmentationEvaluation.jl

Author lucianolorenti
Popularity
2 Stars
Updated Last
1 Year Ago
Started In
May 2018

ImageSegmentationEvaluation

Supervised metrics

  • FBoundary
    • Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues. David R. Martin, Member, IEEE, Charless C. Fowlkes, and Jitendra Malik, Member, IEEE
  • Precision
  • FMeasure
  • Segmentation Covering
  • Variation of Information
  • RandIndex
  • FMeasure for regions
  • Precision Recall for Objects and Parts
    • Measures and Meta-Measures for the Supervised Evaluation of Image Segmentation Jordi Pont-Tuset and Ferran Marques. Universitat Politecnica de Catalunya BarcelonaTech
  • Boundary Displacement Error

References:

Unsupervised metrics

  • ECW
    • The use of visible color difference in the quantitative evaluation of color image segmentation. Hsin-Chia Chen and Sheng-Jyh Wang
  • Zeboudj
    • Zéboudj, Rachid. Filtrage, seuillage automatique, contraste et contours: du pré-traitement à l'analyse d'image. Diss. Saint-Etienne, 1988.
    • Unsupervised Evaluation of Image Segmentation Application to Multi-spectral Images
  • ValuesEntropy
    • An Entropy-based Objective Evaluation Method for Image Segmentation. Hui Zhang*, Jason E. Fritts and Sally A. Goldman
  • LiuYangF
    • Multiresolution Color Image Segmentation. Jianqing Liu and Yee-Hong Yang, Senior Member, IEEE
  • FPrime
    • Quantitative evaluation of color image segmentation results. M. Borsotti a, P. Campadelli a,2, R. Schettini b.
  • Q
    • Quantitative evaluation of color image segmentation results. M. Borsotti a, P. Campadelli a,2, R. Schettini b,
  • FRCRGBD
    • Fusion of geometry and color information for scene segmentation. IEEE Journal of Selected Topics in Signal Processing, 6(5), 505-521. Dal Mutto, C., Zanuttigh, P., & Cortelazzo, G. M. (2012).