Blur-resistant joint 1D and 2D barcode localization for smartphones

Gábor Sörös, C. Floerkemeier
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引用次数: 48

Abstract

With the proliferation of built-in cameras barcode scanning on smartphones has become widespread in both consumer and enterprise domains. To avoid making the user precisely align the barcode at a dedicated position and angle in the camera image, barcode localization algorithms are necessary that quickly scan the image for possible barcode locations and pass those to the actual barcode decoder. In this paper, we present a barcode localization approach that is orientation, scale, and symbology (1D and 2D) invariant and shows better blur invariance than existing approaches while it operates in real time on a smartphone. Previous approaches focused on selected aspects such as orientation invariance and speed for 1D codes or scale invariance for 2D codes. Our combined method relies on the structure matrix and the saturation from the HSV color system. The comparison with three other real-time barcode localization algorithms shows that our approach outperforms the state of the art with respect to symbology and blur invariance at the expense of a reduced speed.
智能手机抗模糊联合1D和2D条码定位
随着内置摄像头的普及,智能手机上的条形码扫描在消费者和企业领域都得到了广泛应用。为了避免让用户将条形码精确地对准相机图像中的特定位置和角度,条形码定位算法是必要的,它可以快速扫描图像以找到可能的条形码位置,并将这些位置传递给实际的条形码解码器。在本文中,我们提出了一种条形码定位方法,该方法具有方向、规模和符号(1D和2D)不变性,并且在智能手机上实时运行时,比现有方法具有更好的模糊不变性。以前的方法侧重于选定的方面,如一维代码的方向不变性和速度,或二维代码的尺度不变性。我们的组合方法依赖于结构矩阵和HSV颜色系统的饱和度。与其他三种实时条形码定位算法的比较表明,我们的方法以降低速度为代价,在符号和模糊不变性方面优于目前的技术水平。
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