A novel approach for edge detection of images

Debashis Ganguly, Swarnendu Mukherjee, Kheyali Mitra, Partha Mukherjee

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

4 Scopus citations

Abstract

Edge detection is a problem of fundamental importance in image analysis. Many approaches for edge detection have already revealed more are waiting to be. But edge detection using K-means algorithm is the most heuristic and unique approach. In this paper, we have proposed an algorithmic technique to detect the edge of any kind of true gray scale images considering the artificial features of the image as the feature set which is fed to K-Means algorithm for clustering the image and there to detect clearly the edges of the objects present in the considered image. The artificial features, which we have considered here, are mean, standard deviation, entropy and busyness of pixel intensity values.Keywords: Edge-detection, K-means algorithm, gray scale images, artificial feature, cluster, mean, standard deviation,entropy, busyness.

Original languageEnglish (US)
Title of host publicationProceedings - 2009 International Conference on Computer and Automation Engineering, ICCAE 2009
Pages49-53
Number of pages5
DOIs
StatePublished - Jun 8 2009
Event2009 International Conference on Computer and Automation Engineering, ICCAE 2009 - Bangkok, Thailand
Duration: Mar 8 2009Mar 10 2009

Publication series

NameProceedings - 2009 International Conference on Computer and Automation Engineering, ICCAE 2009

Conference

Conference2009 International Conference on Computer and Automation Engineering, ICCAE 2009
Country/TerritoryThailand
CityBangkok
Period3/8/093/10/09

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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