文章基本信息

标题：An Optimal Binarization Algorithm Based on Particle Swarm Optimization
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作者：P.Subashini ; N.Sridevi
期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2011
卷号：1
期号：4
页码：32-36
出版社：International Journal of Soft Computing & Engineering
摘要：Document binarization is an active research area for many years. Binarization algorithms play an important role in the preprocessing phase of any character recognition system. This paper compares several alternative binarization algorithms for handwritten documents, by evaluating their performance. The algorithms evaluated are, global thresholding, Otsu thresholding, Kittler-Illingworth and local thresholding, Niblack algorithm along with the proposed PSO algorithm. From the tests and results, we can wrap up with the assumption that the proposed algorithm shows improved results.
关键词：Evaluation; Global thresholding; Image;Binarization; Local thresholding; PSO.