Abstract
In order to enhance the speed, accuracy and robustness of identifying static barcodes, this paper provides an efficient and high-precision barcode recognition technology based on machine vision. This paper analyzes the principle of barcode recognition technology and coding rules, saves the complicated traditional barcode recognition process, and focuses on enhancing barcode recognition. First, grayscale the image, and then use Halcon operators emphasize operator to enhance the image. After debugging the enhancement operator, finally set the MaskWidth of the emphasize operator to 100, MaskHeight to 3, and Factor to 2, the recognition degree is higher under the same conditions, and the system is more robust to static pictures. This system can be applied to book management and warehouse management in various libraries, and provides a faster, more accurate and more robust identification technology for barcode detection.
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Acknowledgements
This work was supported by Innovation Project of Guangxi Graduate Education, grant number GKYC202206, and National Natural Science Foundation of China grant number 51765007.
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Jing, H., Luo, Hp., Zhou, T., Ge, Dy. (2023). Bar-Code Recognition Based on Machine Vision. In: Hu, Z., Wang, Y., He, M. (eds) Advances in Intelligent Systems, Computer Science and Digital Economics IV. CSDEIS 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 158. Springer, Cham. https://doi.org/10.1007/978-3-031-24475-9_1
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DOI: https://doi.org/10.1007/978-3-031-24475-9_1
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