The research of QR code image correction based on image gray feature

Muming Li, Peng Cao, Liuping Feng, Lifang Yu, Jianbo Chen, Jing Wang
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引用次数: 5

Abstract

To solve the problem that traditional geometric correction algorithms of QR code will be influenced by light, shooting impact angle, correction algorithm robustness and so on, this paper proposes an adaptive algorithm based on image gray features, which achieves the accurate reading and rapid correction of QR code location information. After the pre-processing of QR code image, this algorithm calculates the dynamic threshold according to the gray value of feature image and the calculated threshold is used to confirm the most appropriate threshold of the QR location information. Then, we can get four accurate vertexes coordinates of QR code image and accomplish the accurate correction of QR code image based on projection transformation. The algorithm is able to complete effective correction for these captured images under different environments and solve the key technical bottlenecks of QR code recognition.
基于图像灰度特征的二维码图像校正研究
针对传统QR码几何校正算法会受到光线、拍摄冲击角度、校正算法鲁棒性等影响的问题,本文提出了一种基于图像灰度特征的自适应算法,实现了QR码位置信息的准确读取和快速校正。该算法对QR码图像进行预处理后,根据特征图像的灰度值计算动态阈值,并利用计算得到的阈值确定最合适的QR位置信息阈值。然后,我们可以得到QR码图像的四个精确的顶点坐标,并完成基于投影变换的QR码图像的精确校正。该算法能够在不同环境下对这些捕获的图像进行有效的校正,解决了二维码识别的关键技术瓶颈。
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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