Representing space for practical reasoning

Research output: Contribution to journalArticlepeer-review

Abstract

The paper describes a new approach to representing space and time for practical reasoning, based on space-filling cells. Unlike Rn, the new models can represent a bounded region of space using only a finite number of cells, so they can be manipulated directly. Unlike Zn, they have useful notions of function continuity and region 'connectedness'. The topology of space is allowed to depend on the situation being represented, accounting for sharp changes in function values and lack of connectedness across object boundaries. Algorithms based on this model of space are neither purely region based not purely boundary based, but a blend of the two. This new style of algorithm design is illustrated by a new program for finding edges in grey-scale images. Although the program is based on a fairly conventional second directional difference operator, it can detect fine texture in the presence of camera noise, produce connected boundaries around sharp corners and return thin boundaries without 'feathering'. New algorithms are presented for combining directional differences, suppressing the effects of camera noise, reconstructing image intensities from the second difference values and merging results from different scales (including suppression of spurious boundaries in staircase patterns).

Original languageEnglish (US)
Pages (from-to)75-86
Number of pages12
JournalImage and Vision Computing
Volume6
Issue number2
DOIs
StatePublished - May 1988
Externally publishedYes

Keywords

  • edge finding
  • image processing
  • space representation

ASJC Scopus subject areas

  • Signal Processing
  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'Representing space for practical reasoning'. Together they form a unique fingerprint.

Cite this