Vision-Based Localization and Scanning of 1D UPC and EAN Barcodes with Relaxed Pitch, Roll, and Yaw Camera Alignment Constraints
Two algorithms are presented for vision-based localization of 1D UPC and EAN barcodes with relaxed pitch, roll and yaw camera alignment constraints. The first algorithm localizes barcodes in images by computing Dominant Orientations of Gradients (DOGs) of image segments and grouping smaller segments with similar DOGs into larger connected components. Connected components that pass given morphological criteria are marked as potential barcodes. The second algorithm localizes barcodes by growing Edge Alignment Trees (EATs) on binary images with detected edges. EATs of certain sizes mark regions as potential barcodes. The algorithms are implemented in a distributed, cloud-based system. The system's front end is a Smartphone application that runs on Android smartphones with Android 4.2 or higher.