陈柯成,林凡强,邹雪,唐文,杨斯涵,曾财.基于 SDAE 的受损 QR 码恢复算法[J].包装工程,2018,39(15):221-226.
CHEN Ke-cheng,LIN Fan-qiang,ZOU Xue,TANG Wen,YANG Si-han,ZENG Cai.Damaged QR Code Recovery Algorithm Based on SDAE[J].Packaging Engineering,2018,39(15):221-226. |
| 基于 SDAE 的受损 QR 码恢复算法 |
| Damaged QR Code Recovery Algorithm Based on SDAE |
| 投稿时间：2018-03-04 修订日期：2018-08-10 |
| DOI：10.19554/j.cnki.1001-3563.2018.15.035 |
| 中文关键词: 深度学习 堆叠降噪自编码器 图像恢复 QR 码 |
| 英文关键词: deep learning SDAE image restoration QR code |
| 基金项目:成都理工大学 2016 年人才培养质量与教学改革项目（201629） |
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| 中文摘要: |
| 目的 针对包装产品外壳上黑白 QR 码易受到污渍侵蚀损坏，长期磨损易模糊，以及图像采集过程易出现失焦模糊、运动模糊，导致无法完成识别需求，提出一种基于栈式降噪自编码器的受损 QR 码恢复的预处理方法，达到显著修复包装产品上受损的 QR 码图像并提高其识别率的目的。方法 通过深度学习模型栈式降噪自编码器，可以将受到噪声干扰的像素点根据受损像素数据映射到以标准数据为参照的高概率数值点，实现整个受损 QR 码基于像素点的重构恢复，从而提高识别率。结果 通过对实验 QR 码进行高斯模糊、随机污渍侵蚀等多种方式的损坏，能够将识别率较低或完全不能识别的测试图像集恢复出高质量的 QR 码图像，显著地提高了识别率，并且速度快、可重复性好。结论 采用基于栈式降噪自编码器的受损 QR 码恢复的预处理方法，能够重建受损的 QR 码，并可以广泛应用于包装产品 QR 码识别前的预处理，以提高识别率。 |
| 英文摘要: |
| The work aims to propose a pretreatment method based on stacked de-noising autoencoder for the recovery of damaged QR codes, to significantly repair the damaged QR code image on the packaging products and enhance the recognition rate, with respect to the problem that the black-and-white QR code on the shell of the packaging product is prone to be stained, eroded and damaged, and become fuzzy due to long-term wear, and easily subject to out-of-focus blur and motion blur in the process of image acquisition process, leading to the inability to complete identification requirements. Through deep leaning of stacked de-noising autoencoders of the model, the pixels interfered by the noise could be mapped to the high probability numerical point with standard data as reference according to the damaged pixel data, so as to achieve the reconstruction and restoration of the whole damaged QR code based on the pixels, thus improving the recognition rate. Through damages to the experimental QR codes, including Gaussian blur, random stain and erosion, etc., the test image set with low recognition rate or completely unable to be identified could be restored as the high-quality QR code image, significantly improving the recognition rate, featured by fast speed and good repeatability. The pretreatment method based on stacked de-noising autoencoders for the recovery of damaged QR codes can restore the damaged QR code, and be widely applied in the pretreatment before the identification of packaging products' QR code, in order to improve the recognition rate. |
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