Peak detection in Hough transform via self-organizing learning

Sze Tsan Choy, Pui Kin Ser, Wan Chi Siu

Research output: Journal article publicationConference articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

In this paper, we suggest a novel concept of applying the self-organizing map (SOM) in the Hough domain for a significant reduction of the Hough space. By using the SOM as the output space of the generalized Hough transform, the conventional 4-D Hough domain is replaced by a 10 x 10 map, organized in a rectangular grid. Experimental results indicate high accuracy in voting is attainable despite its small memory requirement.
Original languageEnglish
Pages (from-to)139-142
Number of pages4
JournalProceedings - IEEE International Symposium on Circuits and Systems
Volume1
Publication statusPublished - 1 Jan 1995
EventProceedings of the 1995 IEEE International Symposium on Circuits and Systems-ISCAS 95. Part 3 (of 3) - Seattle, WA, United States
Duration: 30 Apr 19953 May 1995

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

Fingerprint

Dive into the research topics of 'Peak detection in Hough transform via self-organizing learning'. Together they form a unique fingerprint.

Cite this