【24h】

Binarization of Stone Inscription Images by Modified Bi-level Entropy Thresholding

机译:基于改进的双层熵阈值对石刻图像进行二值化

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

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.
机译: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,并且为金石学家做出了很大贡献。最近,这些铭文的数字化始于石刻的二元化过程。此过程主要取决于阈值技术。在本文中,陆地和水下石刻图像的二值化之前是对比度增强,然后是基于边缘的滤波,该滤波最大限度地减少了噪点并细化了边缘。该文提出了一种改进的双电平阈值(MBET)算法,并与现有的Otsu方法、Niblack方法、Sauvola方法、Bernsen方法和Fuzzy C均值方法等多种阈值算法进行了比较。使用峰值信噪比 (PSNR) 和标准差 (SD) 等性能指标评估获得的结果。据观察,所提出的方法平均提高了 49% 和 39%,与所考虑的指标相比。

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号