India is rich in its heritage and culture. It has many historical monuments and temples where the walls are made of inscribed stones and rocks. The stone inscriptions play a vital role in portraying about the ancient incidents. Hence, the digitization of these stone inscriptions is necessary and contributes much for the epigraphers. Recently, the digitizing of these inscriptions began with the binarization process of stone inscriptions. This process mainly depends on the thresholding technique. In this paper, the binarization of terrestrial and underwater stone inscription images is preceded by a contrast enhancement and succeeded by edge-based filtering that minimizes noise and fine points the edges. A new method called modified bi-level thresholding (MBET) algorithm is proposed and compared with various existing thresholding algorithms namely Otsu method, Niblack method, Sauvola method, Bernsen method and Fuzzy C means method. The obtained results are evaluated with the performance metrics such as peak signal-to-noise ratio (PSNR) and standard deviation (SD). It is observed that the proposed method has an improvement of 49% and 39%, respectively, on an average by the metrics considered.

中文翻译：

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改进的双层熵阈值对石刻图像的二值化

印度拥有丰富的遗产和文化。它有许多历史古迹和寺庙，墙壁由刻有铭文的石头和岩石制成。石刻在描绘古代事件方面起着至关重要的作用。因此，这些石刻的数字化是必要的，并且对碑文家有很大贡献。最近，这些碑文的数字化是从石碑文的二值化过程开始的。这个过程主要取决于阈值技术。在本文中，陆地和水下石头铭文图像的二值化之前是对比度增强，然后是基于边缘的过滤，可最大限度地减少噪声和精细点边缘。提出了一种新的改进的双层阈值（MBET）算法，并与现有的各种阈值算法Otsu法、Niblack法、Sauvola法、Bernsen法和Fuzzy C均值法进行了比较。使用峰值信噪比 (PSNR) 和标准偏差 (SD) 等性能指标评估获得的结果。可以观察到，所提出的方法在所考虑的指标上平均分别提高了 49% 和 39%。