2020 · 19 citations · 25 references
HumanitiesVision ScienceComputer VisionLocalizationMachine VisionDigital Image ProcessingImage ProcessingVisual LocalizationCamerasCodec DecodingImage ArtifactsNoisy Image RecognitionReal-world Application
In the last decades, many approaches were presented to localize and decode barcodes in images from off the shelf cameras. However, all proposed solutions usually only deal with one type of image artifacts, such as a poorly illuminated or noisy image, or an image that suffers from motion or out-of-focus blur. In this paper, we present a complete, fully automatic pipeline, which allows the localization and decoding of barcodes in real-world scenarios. Our method is capable of localization and decoding the correct barcode information even if the input image is noisy, poorly exposed, and blurred at the same time. We can also decode the correct information from barcode images whose resolution is actually too low, i.e., where the width of the smallest bar depicted is smaller than the width of a single pixel.
25
YOLOv3: An Incremental Improvement
Joseph Redmon, Ali Farhadi · arXiv (Cornell University) · 2018 · 5.9K citations · Full text
Generative Adversarial Networks
arXiv (Cornell University) · 2014 · 4.6K citations · Full text
Scale-Recurrent Network for Deep Image Deblurring
Xin Tao, Hongyun Gao, Xiaoyong Shen et al. · 2018 · 1.3K citations