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首页> 外文会议>International Conference on Document Analysis and Recognition >Low Resolution QR-Code Recognition by Applying Super-Resolution Using the Property of QR-Codes
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Low Resolution QR-Code Recognition by Applying Super-Resolution Using the Property of QR-Codes

机译：通过使用QR码的属性应用超分辨率，通过应用超分辨率的低分辨率QR码识别

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摘要

This paper proposes a method for low resolution QR-code recognition. A QR-code is a two-dimensional binary symbol that can embed various information such as characters and numbers. To recognize a QR-code correctly and stably, the resolution of an input image should be high. In practice, however, recognition of a QR-code is usually difficult due to low resolution when it is captured from a distance. In this paper, we propose a method to improve the performance of low resolution QR-code recognition by using the super-resolution technique that generates a high resolution image from multiple low-resolution images. Although a QR-code is a binary pattern, it is observed as a grayscale image due to the degradation through the capturing process. Especially the pixels around the borders between white and black regions become ambiguous. To overcome this problem, the proposed method introduces a binary pattern constraint to generate super-resolved images appropriate for recognition. Experimental results showed that a recognition rate of 98% can be achieved by the proposed method, which is a 15.7% improvement in comparison with a method using a conventional super-resolution method.
机译：本文提出了一种用于低分辨率QR码识别的方法。 QR码是二维二进制符号，可以嵌入各种信息，例如字符和数字。要正确且稳定地识别QR码，输入图像的分辨率应为高。然而，在实践中，由于在从距离捕获时，识别QR码通常由于低分辨率而困难。在本文中，我们提出了一种通过使用从多个低分辨率图像产生高分辨率图像的超分辨率技术来提高低分辨率QR码识别性能的方法。虽然QR码是二进制图案，但由于通过捕获过程的劣化而被观察为灰度图像。特别是白色和黑色区域之间的边界周围的像素变得模糊。为了克服这个问题，所提出的方法引入了二进制模式约束，以产生适合识别的超分辨图像。实验结果表明，通过所提出的方法可以实现98％的识别率，这是与使用常规超分辨率方法的方法的改善的15.7％。

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