Image Field Categorization and Edge/Corner Detection from Gradient Covariance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mobile Phone Based Interaction with Everyday Products - On the Go
NGMAST '07 Proceedings of the The 2007 International Conference on Next Generation Mobile Applications, Services and Technologies
A simple and efficient approach to barcode localization
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
2D Barcode localization and motion deblurring using a flutter shutter camera
WACV '11 Proceedings of the 2011 IEEE Workshop on Applications of Computer Vision (WACV)
Reading 1D Barcodes with Mobile Phones Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust 1-d barcode recognition on camera phones and mobile product information display
Mobile Multimedia Processing
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With the proliferation of built-in cameras barcode scanning on smartphones has become widespread in both consumer and enterprise domains. To avoid making the user precisely align the barcode at a dedicated position and angle in the camera image, barcode localization algorithms are necessary that quickly scan the image for possible barcode locations and pass those to the actual barcode decoder. In this paper, we present a barcode localization approach that is orientation, scale, and symbology (1D and 2D) invariant and shows better blur invariance than existing approaches while it operates in real time on a smartphone. Previous approaches focused on selected aspects such as orientation invariance and speed for 1D codes or scale invariance for 2D codes. Our combined method relies on the structure matrix and the saturation from the HSV color system. The comparison with three other real-time barcode localization algorithms shows that our approach outperforms the state of the art with respect to symbology and blur invariance at the expense of a reduced speed.