Paper Form Image Recognition Based on SSIM

C. Zhong, Tianxiang Zhou, Ke Wang
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Abstract

This paper introduces a method of filling information recognition for scanned image of paper form. The cross point coordinates are extracted by Strip-like corrosion and expansion of the binary images. The form image base frame is constructed using a rectangular fit based on the Hough transform. Using the image pan, rotate, and scale algorithms, the template form image base frame to the scanned form image base frame can be matched. The filling grid area is determined based on the structural similarity algorithm (SSIM) and the filling information is thus obtained. The experimental results show that this method can accurately, quickly and efficiently read the batch paper form filling information digitally, and has strong robustness.
基于SSIM的纸质表单图像识别
介绍了一种对纸质表格扫描图像进行填充信息识别的方法。通过对二值图像进行带状腐蚀和扩展,提取出交叉点坐标。利用基于霍夫变换的矩形拟合构造了表单图像基帧。利用图像平移、旋转和缩放算法,可以将模板形式的图像基帧与扫描形式的图像基帧进行匹配。根据结构相似度算法(SSIM)确定填充网格区域,从而获得填充信息。实验结果表明,该方法能够准确、快速、高效地读取批量纸质表单填写信息,具有较强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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