| 摘要: |
| 目的 现实生活QR码在识别过程中，易受到非均匀光照因素的影响，导致QR码无法识别，为此提出一种基于二值随机森林的QR码像素值重构算法。方法 依据QR码图像的双峰特点和梯度值相等的特性，用于提取非均匀光照下受损QR码局部像素特征，并利用随机森林的分类方法确定QR码局部矩阵中间单个像素值，逐步实现受损QR码所有像素值的重构恢复。结果 实验表明与其他方法相比，该算法模型能够很好地利用局部特征提取QR码的真实像素值，并对受损QR码图像进行恢复，实验结果图像均具有较高水平。结论 采用基于二值随机森林的QR码重构算法，能够很好地处理因非均匀光照而导致的识别出错问题，并可以广泛应用于生活中的QR码识别过程，具有较强的实用性。 |
| 关键词: 机器学习 随机森林 图像恢复 QR码 |
| DOI：10.19554/j.cnki.1001-3563.2019.11.035 |
| 分类号:TP391.41 |
| 基金项目:成都理工大学2018年度大学生课外科技立项项目（2018KJC0398） |
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| QR Code Reconstruction Algorithm Based on Binary Random Forest under Non-uniform Illumination |
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QIANG Sun-yuan, LI Da-jun, CHEN Ke-cheng, ZENG Cai
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Chengdu University of Technology, Chengdu 610059, China
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| Abstract: |
| The paper aims to propose a QR code pixel value reconstruction algorithm based on binary random forest for real life QR codes which are vulnerable to non-uniform illumination and thus cannot be recognized. According to bimodal features and equal gradient value of QR code image, local pixel features of the damaged QR code under non-uniform illumination were extracted, and a single pixel value in the middle of the local QR code matrix was determined with the random forest classification method, so as to gradually realize reconstruction and recovery of all pixel values of the damaged QR code. The experiment showed that, compared with other methods, this algorithm model can extract the real pixel value of QR code by using local features, and recover the damaged QR code image. The experimental results had high level. The QR code reconstruction algorithm based on binary random forest can deal with the problem of non-uniform illumination recognition error, and can be widely applied to the QR code recognition process in life. It has strong practicability. |
| Key words: machine learning random forest image restoration QR code |
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