Improved Thresholding Method for Enhancing Jawi Binarization Performance
作者： Khairun Saddami , Khairul Munadi , Sayed Muchallil , Fitri Arnia
关键词:
摘要: Most local adaptive image binarization techniques have been inspired by Niblack's method and thus use thresholding. the NICK methods that is based on it introduce a parameter k to determine object boundaries in given window, but one of deficiencies thresholding value constant. In this paper, we propose new approach calculating values for method: set standard deviation image. For our experiments, used DIBCO 2013 dataset privately held ancient Jawi manuscript dataset. The results were evaluated using F-measure, pseudo peak signal-to-noise ratio, misclassication penalty metrics (MPM), distance reciprocal distortion (DRD), overall rank score. proposed achieved result 91.09% 87.07% dataset, which higher than those with earlier fixed ranging from - 0.2 0.1. These indicate produced can adapt state them increase performance.
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