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Automatic Location for Multi-Symbology and Multiple 1D and 2D Barcodes

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並列摘要


Multi-symbology barcode location is a practical and challenging issue. Image-based barcode recognition techniques are robust and extendable approaches for reading versatile one-dimensional (1D) and two-dimensional (2D) barcodes. Most methods may work for a single 1D or 2D barcode or rely on a unique pattern to locate a single 1D or 2D barcode. This work proposes a general localization framework for extraction of real barcodes under complex backgrounds when multiple symbology types exist in the same snapshot for 1D barcodes, 2D barcodes, or both. There are five steps of the proposed algorithm: image grayscale conversion, adaptive thresholding, application of a modified run length smearing algorithm, connected-component labeling, and barcode verification. Experimental results indicate that the proposed approach can locate multiple barcodes and multi-symbology barcodes in complex backgrounds with acceptable accuracy.

參考文獻


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Chen, Y., Yang, Z., Bai, Z. and Wu, J., “Simultaneous Real-time Segmentation of Diversified Barcode Symbols in Complex Background,” First International Workshop on Intelligent Networks and Intelligent Systems (ICINIS '08), pp. 527-530 (2008).
Fang, X., Wu, F., Luo, B., Zhao, H., and Wang, P., “Automatic Recognition of Noisy Code-39 Barcode,” 16th International Conference on Artificial Reality and Telexistence, pp. 79-82 (2006).
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被引用紀錄


林宗儒(2013)。多相關性區域切割研究〔碩士論文,國立臺北大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0023-2808201312151400

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