A NOVEL EDGE DETECTION METHOD USING K-MEANS CLUSTERING

Authors

  • Walaa Mohammed Khalaf Computer & Software Engineering Department, Al-Mustansiriayah University, Baghdad, Iraq Author
  • Kadhum Al-Majdi Computer & Software Engineering Department, Al-Mustansiriayah University, Baghdad, Iraq Author
  • Noor Hashim Hamed Computer & Software Engineering Department, Al-Mustansiriayah University, Baghdad, Iraq Author

Keywords:

edge detection, clustering, image processing

Abstract

In this paper, a new approach is introduced to detect the edges of any kind of grayscale image by using the k-means clustering algorithm, where three novel features are proposed by taking the advantage of the similarity of the image pixel with its eight surrounding neighbors through feeding these features as attributes to the clustering system. This method of edge detection does not use either any smoothing filter or threshold values. The experimental results show that an acceptable detection of the edges is done.

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Key Dates

Published

2016-11-01

How to Cite

A NOVEL EDGE DETECTION METHOD USING K-MEANS CLUSTERING. (2016). Journal of Engineering and Sustainable Development, 20(6), 207-215. https://jeasd.uomustansiriyah.edu.iq/index.php/jeasd/article/view/709

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