| 林叶贵,吴昊,邢科新,何德峰.基于QR码的移动机器人图像自动曝光和识别算法研究[J].高技术通讯(中文),2025,35(10):1100~1107 |
| 基于QR码的移动机器人图像自动曝光和识别算法研究 |
| QR code-based automatic image exposure and recognition algorithm research of mobile robots |
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| DOI：10. 3772 / j. issn. 1002-0470. 2025. 10. 007 |
| 中文关键词: 移动机器人； 二维码； 导航； 图像熵； 曝光算法 |
| 英文关键词: mobile robots, quick response code, navigation, image entropy, exposure algorithm |
| 基金项目: |
| 作者 | 单位 | | 林叶贵 | （浙江工业大学信息工程学院杭州 310023） | | 吴昊 | | | 邢科新 | | | 何德峰 | |
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| 摘要点击次数: 19 |
| 全文下载次数: 42 |
| 中文摘要: |
| 在移动机器人跟踪二维码（quick response，QR）导航过程中，环境及光照的变化会对图像质量有很大的影响，传统依赖于平均灰度的曝光算法很容易因为阈值的变化而失效。曝光时间的选取对二维码识别效果的影响非常大。针对这些问题，设计了基于融合图像熵、平均灰度和直方图的自动曝光算法，根据环境及光照变化自动选择最佳曝光时间，获得高质量的曝光图片。为了提高二维码定位速度和识别效率，提出了一种新的二维码识别算法，该算法将二维码检测识别速度提高了12%。实验结果表明，本文所提算法提高了移动机器人二维码识别的速度和跟踪效率。 |
| 英文摘要: |
| In quick response (QR) code-based navigation tracking of mobile robots, the changes of environment and illumination have a great impact on image quality of QR code. The traditional exposure algorithm relying on average grayscale can easily fail due to the changes of thresholds. Moreover, the exposure time has a great influence on the efficiency of QR code recognition. In this paper, an automatic exposure algorithm is designed using the fusion of image entropy, average gray level and histogram. Then the optimal exposure time is automatically computed to accommodate the environment and illumination changes. In order to improve the QR code detection speed and recognition efficiency, a new QR code recognition algorithm is designed to improve the speed of QR code detection and recognition by 12%. The experimental results show that the proposed algorithm improves the speed of QR code recognition and the tracking efficiency of mobile robots. |
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