An efficient iterative algorithm for image thresholding

Authors:
Liju Dong;Ge Yu;Philip Ogunbona;Wanqing Li
Affiliations:
School of Information Science and Engineering, Shenyang University, Shenyang, PR China;School of Information Science and Engineering, Northeastern University, Shenyang, PR China;School of Computer Science and Software Engineering, University of Wollongong, Wollongong, Australia;School of Computer Science and Software Engineering, University of Wollongong, Wollongong, Australia
Venue:
Pattern Recognition Letters
Year:
2008

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Abstract

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 Otsu's 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 Otsu's algorithm. Experimental results have verified the theoretical analysis and the efficiency of the proposed algorithm.