基于Halcon图像分析的快递信息识别
Express Information Recognition Based on Halcon Image Analysis
DOI: 10.12677/SEA.2022.113046, PDF,    科研立项经费支持
作者: 吴海升, 张有中:厦门大学嘉庚学院管理学院,福建 漳州
关键词: 快递信息Halcon一维码识别拉普拉斯算子Express Information Halcon One Dimensional Code Recognition Laplace Operator
摘要: 本文基于Halcon的图像分析,发展对快递面单的图像进行获取、分割、提取有效特征的方法,实现对快递面单的信息识别技术,并验证其有效性与准确性。研究首先通过工业相机获取快递面单照片,然后创建一维模型,检测条码首尾空白区域,并利用拉普拉斯算子提取条码边缘轮廓,获取条码类型、信息,进行识别判读。结果发现快递面单一维码信息识别与真正的快递单号结果一致,验证Halcon软件应用于快递面单信息识别技术确实可行,能够以机器视觉的识别方式取代快递的人工分捡工作。
Abstract: Based on Halcon image analysis technology, this paper develops the methods of acquiring, segmenting and extracting effective features from the images of express information sheets, realizes the information recognition technology of express information sheets, and verifies its effectiveness and accuracy. Firstly, the photo of express information sheet is obtained by industrial camera, then a one-dimensional code model is created to detect the blank area at the beginning and end of the bar code, and the edge contour of the bar code is extracted by Laplace operator to obtain the type and information of the bar code. The results of this research show that the one-dimensional code information recognition of express order is consistent with the real express order number. It is verified that the application of Halcon software to express information sheet recognition technology is indeed feasible, and can replace the manual sorting of express with the recognition method of machine vision.
文章引用:吴海升, 张有中. 基于Halcon图像分析的快递信息识别[J]. 软件工程与应用, 2022, 11(3): 435-444. https://doi.org/10.12677/SEA.2022.113046

参考文献

[1] 高雅, 秦文华, 代作晓, 等. 基于机器视觉的纸杯缺陷检测系统设计[J]. 电子技术(上海), 2017, 46(8): 3.
[2] 曾志鸿, 刘军. 基于HALCON的快递地址信息识别研究[J]. 机电信息, 2019(17): 1-3.
[3] 叶雷锋. 论信息技术在现代物流管理中的重要性[J]. 中国西部科技, 2008, 7(36): 2.
[4] 马继成, 阮学云. 基于Halcon, 组态王和PLC的快递分拣系统的设计[J]. 工业控制计算机, 2019, 32(9): 36-37.
[5] 吴雪芬, 李昊昱, 陈功, 等. HALCON软件在车牌图像处理中的应用[J]. 电子质量, 2014(12): 49-54.
[6] 戴仲豪, 王泽进, 陈厚儒, 等. 基于HALCON的水果识别算法研究[J]. 机械工程师, 2018(12): 4.
[7] 任鹏霏, 周传德, 胡帅, 等. HALCON图像处理在纸杯缺陷检测中的应用[J]. 自动化应用, 2019(6): 3.
[8] 耿立明, 杨威, 王迪. HALCON图像处理在机器视觉中的应用[J]. 电子测试, 2019(1): 2.
[9] Milan, S. (2007) Image Processing, Analysis, and Machine Vision. Thomson-Engineering.
[10] 张伟超. 基于HALCON的PCB缺陷在线视觉检测系统[D]: [硕士学位论文]. 济南: 齐鲁工业大学, 2021.
[11] Wildes, R.P., Asmuth, J.C., Green, G.L., Hsu, S.C., and Kolczynski, R.J. (1996) A Machine-Vision System for Iris Recognition. Machine Vision & Applications, 9, 1-8. [Google Scholar] [CrossRef
[12] Cubero, S., Aleixos, N., Moltó, E., Gómez-Sanchis, J. and Blasco, J. (2010) Advances in Machine Vision Applications for Automatic Inspection and Quality Evaluation of Fruits and Vegetables. Food and Bioprocess Technology, 4, 487-504. [Google Scholar] [CrossRef