Multiple Barcode Detection with Mask R-CNN
Enes Polat, Hussein M.A. Mohammed, Aslı Nur Ömeroğlu, Nida Kumbasar, İbrahim Yücel Özbek, Emin Argun Oral · 2020
Almost all products on the market today have a unique code or ID associated with them. This special identification is called a barcode. Barcodes have been the subject of extensive research in recent years due to the high demand for automation in various industrial environments. Fast and accurate reading of barcodes, where all details about the product used in many commercial applications can be learned, is very important. In this study, Mask R-CNN algorithm was used to determine the regions of the 1B barcodes in the image. In the Mask R-CNN, barcodes in the image have been detected, as well as the bounding box position of each barcode, as well as the pixel information corresponding to this class in the bounding box. Colored barcodes on various products taken at different ambient lights and at different angles were collected and a data set of 1114 images was prepared. Using this dataset, 74.41 % accuracy was achieved with Mask R-CNN.