一种改进的羊皮纸老年人手迹识别分割算法
Modified Segmentation Algorithm for Recognition of Older Geez Scripts Written on Vellum
摘要：
手写文档识别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研究方向。当一份文件在几百年前写在牛皮纸上时，它就变得更加复杂了，就像更古老的吉兹脚本一样。在这项研究中，我们介绍了一种改进的分割方法来识别旧的吉兹脚本。我们使用自适应滤波降噪，Isodata迭代全局阈值的文档图像二值化，修改限界框投影分割Geez字符，数字和标点符号之间的不同笔画。SVM多类分类器在改进的分割算法下获得了79.32%的识别准确率。
英文摘要：
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.
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