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Edge detection for Chinese text image based on novel differential operator

机译:基于新型微分算子的中文文本图像边缘检测

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Consisted with the fast development of digital information technique, the historical paper-base documents haven been planned and executed to be scanned and digitalized. Transformation of the detected character signal into binary codes is essentially decided by the edge detection procedure. Though there have some reports about English alphabet detection, few focused on the Chinese text. In this paper, the differential operator method is put forward to detect the image edge based on the step change between strokes and the grey background. After analyzing the traditional operators, which is effective to detect simple scenery image but deteriorating the Chinese text, novel 5×5 dimensional differential operator is proposed. Results verify that the novel operator is more effective than the custom ones in edge restoration of Chinese stoke. Also, it presents that the denoise procedure is necessary to improve the pixel weighted average performance of the differential operator. The novel operator can be integrated in Optical Character Recognition (OCR) system as preprocessing element.
机译:随着数字信息技术的飞速发展,历史性的纸质文档尚未被计划和执行以进行扫描和数字化。所检测的字符信号到二进制代码的转换基本上由边缘检测过程决定。尽管有一些有关英文字母检测的报告,但很少有针对中文文本的报告。提出了一种基于算子和灰色背景之间的阶跃变化的差分算子方法来检测图像边缘。在分析了传统算子的基础上,提出了一种新颖的5×5维微分算子,该算子可以有效地检测出简单的风景图像,但对中文文字质量却有很大的影响。结果证明,该新型算子在自定义笔画的边缘恢复中比自定义算子更有效。而且,它提出去噪过程对于改善差分算子的像素加权平均性能是必要的。可以将新型运算符集成到光学字符识别(OCR)系统中作为预处理元素。

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