Text Recognition of Cardboard Pharmaceutical Packages by Utilizing Machine Vision

Text Recognition of Cardboard Pharmaceutical Packages by Utilizing Machine Vision
复制标题

利用机器视觉对纸板药品包装进行文本识别

DOI：
10.2352/issn.2470-1173.2021.10.ipas-235
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发表时间：
2021
期刊：
International Conference on Image Processing, Applications and Systems
影响因子：
--
通讯作者：
P. Toivanen
P. Toivanen
中科院分区：
--
文献类型：
--
作者：
Jarmo Koponen;Keijo Haataja;P. Toivanen

文献摘要

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本文从光度立体成像的角度研究了可变弯曲纸板药品包装的文本识别，重点开发了一种对有效期和批次代码文本进行二值化的方法。自适应滤波，更具体地说是维纳滤波 过滤器与除雾算法一起使用，融合 LoG 边缘检测到的子图像，生成过期日期和批次代码文本的 Otsu 阈值二进制图像，以供将来分析。给出了一些结果，它们似乎对文本二值化很有希望。成功 二值化对于文本字符分割和进一步的自动阅读至关重要。此外，还将提出一些新的想法，这些想法将用于我们未来的研究工作。
In this paper, text recognition of variably curved cardboard pharmaceutical packages is studied from the photometric stereo imaging point-of-view with focus on developing a method for binarizing the expiration date and batch code texts. Adaptive filtering, more specifically Wiener filter, is used together with haze removal algorithm with fusion of LoG-edge detected sub-images resulting an Otsu thresholded binary image of expiration date and batch code texts for future analysis. Some results are presented, and they appear to be promising for text binarization. Successful binarization is crucial in text character segmentation and further automatic reading. Furthermore, some new ideas will be presented that will be used in our future research work.