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An Algorithm for In-Place Vision-Based Skewed ID Barcode Scanning in the Cloud

机译:一种基于视觉的基于视觉的偏移ID条码扫描算法

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An algorithm is presented for in-place vision-based skewed 1D barcode scanning that requires no smartphone camera alignment. The algorithm is in-place in that it performs no rotation of input images to align localized barcodes for scanning. The algorithm is cloud-based, because image processing is done in the cloud. The algorithm is implemented in a distributed, cloud-based system. The system's front end is a smartphone application that runs on Android 4.3 or higher. The system's back end is currently deployed on a four node Linux cluster used for image recognition and data storage. The algorithm was evaluated on a set of 506 video recordings of common grocery products. The videos had a 1280 × 720 resolution, an average duration of 15 seconds, and were recorded on an Android Galaxy Nexus smartphone in a local supermarket. The results of the experiments are presented and discussed.
机译:提出了一种算法,用于基于视觉的基于视觉的偏斜1D条形码扫描,其不需要智能手机相机对齐。该算法在其内部不执行输入图像的旋转以对准局部条形码以进行扫描。算法基于云,因为在云中完成了图像处理。该算法在分布式的基于云的系统中实现。系统的前端是一个在Android 4.3或更高版本上运行的智能手机应用程序。系统的后端目前部署在用于图像识别和数据存储的四节点Linux群集上。该算法在普通杂货产品的一组506录像录制上进行了评估。该视频具有1280×720分辨率,平均持续时间为15秒,并记录在当地超市的Android Galaxy Nexus智能手机上。提出并讨论了实验结果。

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