论文标题
修改的分割算法，用于识别在牛皮纸上写的旧geez脚本
Modified Segmentation Algorithm for Recognition of Older Geez Scripts Written on Vellum
论文作者
论文摘要
识别手写文档的目的是将文档图像转换为机器可理解的格式。手写文档识别是模式识别领域中最具挑战性的领域。像较旧的geez脚本一样，当文档写在牛皮纸上时，它变得更加复杂。在这项研究中，我们引入了一种修改的细分方法，以识别较旧的geez脚本。我们使用自适应滤波来减少噪声，ISODATA迭代全局阈值进行文档图像二进制，修改后的边界框投影到geez字符，数字和标点符号之间的段不同笔触。 SVM多类分类器通过修改的分割算法得分为79.32％的识别精度。
Recognition of handwritten document aims at transforming document images into a machine understandable format. Handwritten document recognition is the most challenging area in the field of pattern recognition. It becomes more complex when a document was written on vellum before hundreds of years, like older Geez scripts. In this study, we introduced a modified segmentation approach to recognize older Geez scripts. We used adaptive filtering for noise reduction, Isodata iterative global thresholding for document image binarization, modified bounding box projection to segment distinct strokes between Geez characters, numbers, and punctuation marks. SVM multiclass classifier scored 79.32% recognition accuracy with the modified segmentation algorithm.
