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An efficient iterative algorithm for image thresholding
Pattern Recognition Letters
  • Liju Dong, Shenyang University
  • Ge Yu, Northeastern University
  • Philip O Ogunbona, University of Wollongong
  • Wanqing Li, University of Wollongong
Document Type
Journal Article
Publication Date

Thresholding is a commonly used technique for image segmentation. This paper presents an efficient iterative algorithm for finding optimal thresholds that minimize a weighted sum-of-squared-error objective function. We have proven that the proposed algorithm is mathematically equivalent to the well-known Otsus method, but requires much less computation. The computational complexity of the proposed algorithm is linear with respect to the number of thresholds to be calculated as against the exponential complexity of the Otsus algorithm. Experimental results have verified the theoretical analysis and the efficiency of the proposed algorithm.

Citation Information
Liju Dong, Ge Yu, Philip O Ogunbona and Wanqing Li. "An efficient iterative algorithm for image thresholding" Pattern Recognition Letters Vol. 29 Iss. 9 (2008) p. 1311 - 1316
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