Error measures for scene segmentation

William A. Yasnoff, Jack K. Mui, James W. Bacus

Research output: Contribution to journalArticlepeer-review

Abstract

Scene segmentation is an important problem in pattern recognition. Current subjective methods for evaluation and comparison of scene segmentation techniques are inadequate and objective quantitative measures are desirable. Two error measures, the percentage area misclassified (p) and a new pixel distance error (ε{lunate}) were defined and evaluated in terms of their correlation with human observation for comparison of multiple segmentations of the same scene and multiple scenes segmented by the same technique. The results indicate that both these measures can be helpful in the evaluation and comparison of scene segmentation procedures.

Original languageEnglish (US)
Pages (from-to)217-231
Number of pages15
JournalPattern Recognition
Volume9
Issue number4
DOIs
StatePublished - 1977
Externally publishedYes

Keywords

  • Blood cells
  • Confusion matrix
  • Error measures
  • Image processing
  • Pixel distance error
  • Psychopictorics
  • Scene segmentation
  • Type I and II error

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Electrical and Electronic Engineering

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