Detecting corners of polygonal and polyhedral objects

Jinn Kwei Guo, Rein Lien Hsu, Chin Hsing Chen, Yung Nein Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this paper, we proposed a novel corner detection algorithm, based on statistical properties of corners, to detect corners of both polygonal and polyhedral objects. By means of local histogram analysis, we first bilevel the subimage within a circular window, then compute the intensity mean for the bileveled subimage. From the intensity mean we can estimate the corner angle. We then calculate the theoretical position variance from the estimated angle. Comparing the position variance from the bileveled subimage with its theoretical value, we can identify whether or not the pixel at the center of the subimage is a corner. Finally, the corner orientation can be obtained from the position mean. Our algorithm can detect corners of both polygons and polyhedra, even if they appear in an image at the same time. It is superior to conventional detection algorithms that it can detect corners over a large range of angles.

Original languageEnglish
Title of host publicationComputer Analysis of Images and Patterns - 5th International Conference, CAIP 1993, Proceedings
EditorsDmitry Chetverikov, Walter G. Kropatsch
PublisherSpringer Verlag
Number of pages8
ISBN (Print)9783540572336
Publication statusPublished - 1993
Event5th International Conference on Computer Analysis of Images and Patterns, CAIP 1993 - Budapest, Hungary
Duration: 1993 Sept 131993 Sept 15

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume719 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other5th International Conference on Computer Analysis of Images and Patterns, CAIP 1993

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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