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Barcode Localization With Region-Based Gradient Statistical Analysis

机译：基于区域梯度统计分析的条形码定位

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摘要

Barcode, as a kind of data representation method, has been adopted in a wide range of areas. Especially with the rise of the smart phone and the hand-held device equipped with high resolution camera and great computation power, barcode technique has found itself more extensive applications. In industrial field, barcode reading system is highly demanded to be robust to blur, illumination change, pitch, rotation, and scale change. This paper gives a new idea in localizing barcode under a region-based gradient statistical analysis. Making this idea as the basis, four algorithms have been developed for dealing with Linear, PDF417, Stacked 1D1D and Stacked 1D2D barcodes respectively. After being evaluated on our challenging dataset with more than 17000 images, the result shows that our methods can achieve an average localization accuracy of 82.17% with respect to 8 kinds of distortions and within an average time of 12 ms.
机译：条形码作为一种数据表示方法，已经在广泛的领域中得到采用。尤其是随着智能电话和配备了高分辨率摄像头和强大计算能力的手持设备的兴起，条形码技术已经发现了更广泛的应用。在工业领域中，高度要求条形码读取系统具有鲁棒性以防模糊，照度变化，间距，旋转和比例变化。本文提出了一种基于区域梯度统计分析的条形码定位新思路。以这个想法为基础，已经开发了四种算法分别用于处理线性，PDF417，堆叠的1D1D和堆叠的1D2D条形码。在具有17000多个图像的具有挑战性的数据集上进行评估后，结果表明，相对于8种失真，我们的方法在12毫秒的平均时间内可以实现82.17％的平均定位精度。

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