Fast Iterative Algorithm for Two-Dimensional Otsu Thresholding Method
WU Cheng-Mao1,2, TIAN Xiao-Ping1,2, TAN Tie-Niu2
1.Department of Electronics and Information Engineering, Xi'an Institute of Post and Telecommunications, Xi'an 7101212. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190
Abstract:A fast iterative algorithm for two-dimensional Otsu thresholding method is proposed. Considering the disadvantages of the classical two-dimensional Otsu thresholding method and its recursive algorithm, it is supposed that the two-dimensional histogram which is composed of original segmented image and its local neighborhood average image is a two-variable continuous probability distribution function. The method for seeking extreme value of multivariate function is employed and the fast iterated algorithm of two-dimensional Otsu thresholding method is obtained. The experimental results show that the proposed fast iterative algorithm is feasible and has better segmentation performance.
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