An efficient iterative algorithm for image thresholdingPattern Recognition Letters
Document TypeJournal Article
AbstractThresholding 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 InformationLiju 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
Available at: http://works.bepress.com/p_ogunbona/12/