Improved Co-occurrence Matrix as a Feature Space for Relative Entropy-based Image Thresholding

  • Authors:

  • I. El-Feghi;N. Adem;M. A. Sid-Ahmed;M. Ahmadi

  • Affiliations:

  • Higher Industrial Insitutte, Misurata-Libya;El-Fath University, Tripoli-Libya;University of Windsor, Canada;University of Windsor, Canada

  • Venue:
  • CGIV '07 Proceedings of the Computer Graphics, Imaging and Visualisation
  • Year:
  • 2007

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Abstract

In this paper, a thresholding technique suitable for noisy background images is proposed. The proposed algorithm uses an improved co-occurrence matrix as feature spaces. The threshold value is obtained by maximizing the relative entropy. Experimental results show that the proposed method outperforms other thresholding techniques especially on the presences of noise in the background of the input image.