A Novel Metric on Partitions for Image Segmentation

  • Authors:

  • Vladimir Mashtalir;Elena Mikhnova;Vladislav Shlyakhov;Elena Yegorova

  • Affiliations:

  • Kharkov National University of Radio Electronics, Ukraine;Kharkov National University of Radio Electronics, Ukraine;Kharkov National University of Radio Electronics, Ukraine;Kharkov National University of Radio Electronics, Ukraine

  • Venue:
  • AVSS '06 Proceedings of the IEEE International Conference on Video and Signal Based Surveillance
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

The explosion of image content is closely connected with segmentations efficiency. However, there is no agreement as to what a good segmentation is due to hard data and applications dependence. To reduce the gap between low-level features and high-level semantic, collections of image partitions produced by different segmentation algorithms are often considered. We propose, theoretically ground and experimentally explore a new metric on segmented images or on arbitrary partitions of finite sets in general.