期刊名称：Signal & Image Processing : An International Journal (SIPIJ)
印刷版ISSN：2229-3922
电子版ISSN：0976-710X
出版年度：2017
卷号：8
期号：4
页码：15
DOI：10.5121/sipij.2017.8402
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Aim of this paper is reformulation of global image thresholding problem as a well-founded statisticalmethod known as change-point detection (CPD) problem. Our proposed CPD thresholding algorithm doesnot assume any prior statistical distribution of background and object grey levels. Further, this method isless influenced by an outlier due to our judicious derivation of a robust criterion function depending onKullback-Leibler (KL) divergence measure. Experimental result shows efficacy of proposed methodcompared to other popular methods available for global image thresholding. In this paper we also proposea performance criterion for comparison of thresholding algorithms. This performance criteria does notdepend on any ground truth image. We have used this performance criterion to compare the results ofproposed thresholding algorithm with most cited global thresholding algorithms in the literature.
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