TY - GEN
T1 - Bar code recognition in highly distorted and low resolution images
AU - Shams, Ramtin
AU - Sadeghi, Parastoo
PY - 2007
Y1 - 2007
N2 - In this paper, we present a novel approach to detection of one dimensional bar code images. Our algorithm is particularly designed to recognize bar codes, where the image may be of low resolution, low quality or suffer from substantial blurring, de-focusing, non-uniform illumination, noise and color saturation. The algoritnni is accurate, fast, scalable and can be easily adjusted to search for a valid result within a specified time constraint. Our algorithm is particulary useful for real-time recognition of bar codes in portable hand-held devices with limited processing capability, such as mobile phones.
AB - In this paper, we present a novel approach to detection of one dimensional bar code images. Our algorithm is particularly designed to recognize bar codes, where the image may be of low resolution, low quality or suffer from substantial blurring, de-focusing, non-uniform illumination, noise and color saturation. The algoritnni is accurate, fast, scalable and can be easily adjusted to search for a valid result within a specified time constraint. Our algorithm is particulary useful for real-time recognition of bar codes in portable hand-held devices with limited processing capability, such as mobile phones.
KW - Bar codes
KW - Feature extraction
KW - Image segmentation
KW - Pattern recognition
KW - Peak detection
UR - http://www.scopus.com/inward/record.url?scp=34547514839&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2007.366013
DO - 10.1109/ICASSP.2007.366013
M3 - Conference contribution
SN - 1424407281
SN - 9781424407286
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - I737-I740
BT - 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
T2 - 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
Y2 - 15 April 2007 through 20 April 2007
ER -