一种基于子块 OSTU 和改进的 Sauvola 的快速自适应二值化方法

2019-8-17 12:22| 发布者: 迪杰管理| 查看: 10349| 评论: 0

摘要: 迪杰网讯 A Fast Adaptive Binarization Method Based on Sub Block OSTU and Improved Sauvola 本文提出了一种新颖的混合二值化方法,其实将全局阈值法和局部自适应阈值相结合,并用于前景和背景的分割。在全局阈值 ...

迪杰网讯 A Fast Adaptive Binarization Method Based on Sub Block OSTU and Improved Sauvola


本文提出了一种新颖的混合二值化方法,其实将全局阈值法和局部自适应阈值相结合,并用于前景和背景的分割。在全局阈值分割中,子块OSTU用来获得表达局部分布特性的更好,而全局OSTU方法则不能。在源图像和二值化图像中对局部子块分别进行扫描以便进行进一步处理。sauvola算法运用于整个图像以对其进行进一步二值化处理。对几种印刷信封实例的仿真结果表明,该算法可以保持与改进的sauvola算法相同的性能的同时,减少了27.4%的处理时间。


This paper has advanced a novel hybrid binarization method combining global thresholding and local adaptive thresholding used for foreground and background segmenting. In global thresholding, sub block OSTU is used to achieve better performance for it can represent local distribution characteristics while global OSTU method cannot. Original image and binary image are scanned individually to locate sub blocks which require further process. Sauvola algorithm implementing integral image is then performed for a second binarization. Simulation results on several printform envelopes show that this algorithm can maintain the same performance with the improved Sauvola algorithm while reducing the processing time by 27.4%.


本文发表在:7th International Conference on Wireless Communications, Networking and Mobile Computing,WiCOM 2011,EI index。


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