The DSC algorithm for edge detection

Jonghoon Oh, Chang-Sung Jeong

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

2 Citations (Scopus)

Abstract

Edge detection is one of the fundamental operations in computer vision with numerous approaches to it. In nowadays, many algorithms for edge detection have been proposed. However, most conventional techniques have assumed clear images or Gaussian noise images, thus their performance could decrease with the impulse noise. In this paper, we present an edge detection approach using Discrete Singular Convolution algorithm. The DSC algorithm efficiently detects edges not only original images but also noisy images which are added by Gaussian and impulse noise. Therefore, we evaluate that the performance of the DSC algorithm is compared with other algorithms such as the Canny, Bergholm, and Rothwell algorithm.

Original languageEnglish
Title of host publicationLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
EditorsG.I. Webb, X. Yu
Pages967-972
Number of pages6
Volume3339
Publication statusPublished - 2004
Event17th Australian Joint Conference on Artificial Intelligence, AI 2004: Advances in Artificial Intelligence - Cairns, Australia
Duration: 2004 Dec 42004 Dec 6

Other

Other17th Australian Joint Conference on Artificial Intelligence, AI 2004: Advances in Artificial Intelligence
CountryAustralia
CityCairns
Period04/12/404/12/6

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ASJC Scopus subject areas

  • Hardware and Architecture

Cite this

Oh, J., & Jeong, C-S. (2004). The DSC algorithm for edge detection. In G. I. Webb, & X. Yu (Eds.), Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3339, pp. 967-972)