Color image edge detection using cluster analysis

Hai Tao, Thomas S Huang

Research output: Contribution to conferencePaper

Abstract

A color image edge detection algorithm is proposed in this paper based on the idea that use global color information to guide local gradient computation. Major chromatic components of an image are first extracted through cluster analysis. According to these color clusters, a set of linear chromatic transforms are generated. An appropriate chromatic transform is chosen for each pixel to maximize the gradient magnitude. In this way, edges are treated as transitions from one cluster to another. The algorithm is implemented and experimental results for real color images are included.

Original languageEnglish (US)
Pages834-836
Number of pages3
StatePublished - Dec 1 1997
EventProceedings of the 1997 International Conference on Image Processing. Part 2 (of 3) - Santa Barbara, CA, USA
Duration: Oct 26 1997Oct 29 1997

Other

OtherProceedings of the 1997 International Conference on Image Processing. Part 2 (of 3)
CitySanta Barbara, CA, USA
Period10/26/9710/29/97

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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  • Cite this

    Tao, H., & Huang, T. S. (1997). Color image edge detection using cluster analysis. 834-836. Paper presented at Proceedings of the 1997 International Conference on Image Processing. Part 2 (of 3), Santa Barbara, CA, USA, .