DocumentCode :
270285
Title :
GPU-accelerated joint 1D and 2D barcode localization on smartphones
Author :
Sörös, Gábor
Author_Institution :
Dept. of Comput. Sci., ETH Zurich, Zurich, Switzerland
fYear :
2014
fDate :
4-9 May 2014
Firstpage :
5095
Lastpage :
5099
Abstract :
The built-in cameras and powerful processors have turned smartphones into ubiquitous barcode scanners. In smartphone-based barcode scanning, barcode localization is an important preprocessing step that quickly scans the entire camera image and passes barcode candidates to the actual decoder. This paper presents the implementation steps of a robust joint 1D and 2D barcode localization algorithm on the mobile GPU. The barcode probability maps are derived from the structure matrix and the color of the individual pixels. The different steps of the localization algorithm are formulated as OpenGL ES 2.0 fragment shaders and both 1D and 2D barcode saliency maps are computed directly on the graphics hardware. The presented method can detect barcodes at various scales and orientations at 6 frames per second in HD resolution images on current generation smartphones.
Keywords :
bar codes; computer graphics; decoding; graphics processing units; image coding; image colour analysis; mark scanning equipment; probability; smart phones; ubiquitous computing; 1D barcode saliency maps; 2D barcode saliency maps; OpenGL ES 2.0 fragment shaders; barcode probability maps; built-in cameras; camera image; decoder; graphics hardware; individual pixel color; joint 1D barcode localization; joint 2D barcode localization; localization algorithm; mobile GPU; processors; smartphone-based barcode scanning; structure matrix; ubiquitous barcode scanners; Cameras; Decoding; Graphics processing units; Hardware; Image color analysis; Mobile communication; Smart phones; GPGPU; QR code; barcode; localization; smartphone;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location :
Florence
Type :
conf
DOI :
10.1109/ICASSP.2014.6854573
Filename :
6854573
Link To Document :
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