Title :
Peak classifier for bar code waveforms
Author :
Joesph, E. ; Pavlidis, Theo
Author_Institution :
Dept. of Comput. Sci., State Univ. of New York, Stony Brook, NY, USA
fDate :
30 Aug-3 Sep 1992
Abstract :
Previous bar code decoding algorithms operated on the binarized output of a hardware digitizer which limited the working range of the algorithm. The authors propose a new and more aggressive bar code decoder that operates on the location of the peaks of the bar code waveform. This algorithm can operate in high convolution distortion environments and is based on statistical pattern recognition techniques. However no training data is required and the misdecode rate is controlled by a single adjustable parameter
Keywords :
bar codes; decoding; image recognition; statistical analysis; bar code waveforms; convolution distortion environments; decoding; peak classifier; statistical pattern recognition; Computer vision; Convolution; Decoding; Distortion measurement; Hardware; Image edge detection; Pattern recognition; Shape; Table lookup; Training data;
Conference_Titel :
Pattern Recognition, 1992. Vol.II. Conference B: Pattern Recognition Methodology and Systems, Proceedings., 11th IAPR International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-8186-2915-0
DOI :
10.1109/ICPR.1992.201763