Tekin Ender, Coughlan James
The Smith-Kettlewell Eye Research Institute.
Proc Can Conf Comput Robot Vis. 2009 May 25;2009:61-67. doi: 10.1109/CRV.2009.31.
The 1D barcode is a ubiquitous labeling technology, with symbologies such as UPC used to label approximately 99% of all packaged goods in the US. It would be very convenient for consumers to be able to read these barcodes using portable cameras (e.g. mobile phones), but the limited quality and resolution of images taken by these cameras often make it difficult to read the barcodes accurately. We propose a Bayesian framework for reading 1D barcodes that models the shape and appearance of barcodes, allowing for geometric distortions and image noise, and exploiting the redundant information contained in the parity digit. An important feature of our framework is that it doesn't require that every barcode edge be detected in the image. Experiments on a publicly available dataset of barcode images explore the range of images that are readable, and comparisons with two commercial readers demonstrate the superior performance of our algorithm.
一维条形码是一种无处不在的标签技术，其符号体系如通用产品代码（UPC）被用于给美国约99%的包装商品贴标签。消费者若能用便携式相机（如手机）读取这些条形码会非常方便，但这些相机拍摄的图像质量和分辨率有限，常常难以准确读取条形码。我们提出了一个用于读取一维条形码的贝叶斯框架，该框架对条形码的形状和外观进行建模，考虑到几何失真和图像噪声，并利用校验位中包含的冗余信息。我们框架的一个重要特点是它不要求在图像中检测出每个条形码边缘。在一个公开可用的条形码图像数据集上进行的实验探索了可读图像的范围，与两款商业阅读器的比较证明了我们算法的优越性能。
