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A New Text-Line Alignment Approach Based on Piece-Wise Painting Algorithm for Handwritten Documents

机译:一种基于手写文档的典型绘画算法的新型文本线对齐方法

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Because of writing styles of different individuals, some of the text-lines may be curved in shape. For recognition of such text-lines, their proper alignment is necessary. In this paper, we propose a text-line alignment technique based on painting algorithm. Here at first, Piece-wise Painting Algorithm (PPA) is used to get a number of black and white rectangular patches all along the text-line for text-line alignment. Identifying the degree of oscillation of the input text-line, some candidate pixels are also obtained based on horizontal projection and center points of the black patches. Using the degree of oscillation of the input text image and the candidate pixels a curve or straight line is fit to trace the baseline. Subsequently, all components of the text-line are deskewed based on analyzing the characteristic of the fit curve or line to align the components with respect to the horizontal imaginary baseline. The proposed algorithm was evaluated with 128 Persian handwritten text-lines containing 4317 sub words. Experimental analysis showed that 92.31% of the sub words were accurately aligned. Further, the proposed algorithm was tested with another Persian handwritten text-lines dataset [6] and remarkable results were achieved.
机译:由于写入不同个体的样式,一些文本线可以是弯曲的。为了识别这种文本线,需要正确的对齐。本文提出了一种基于绘画算法的文本线对准技术。首先,在这里,术语绘画算法(PPA)用于获得沿着文本线路沿文本线对齐的多个黑白矩形贴片。识别输入文本线的振荡程度,还基于黑色斑块的水平投影和中心点获得一些候选像素。使用输入文本图像的振荡程度和候选像素曲线或直线适合追踪基线。随后,基于分析拟合曲线或线的特性来对其对对准水平假想基线对准组件来倾斜的所有组件。该算法用128个Persian手写文本线进行了评估,其中包含4317个子字。实验分析表明,92.31%的子词精确对齐。此外,使用另一个波斯手写的文本线数据集[6]测试了所提出的算法,实现了显着的结果。

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