Title :
Bar Code Recognition in Highly Distorted and Low Resolution Images
Author :
Shams, Reza ; Sadeghi, Parastoo
Author_Institution :
Res. Sch. of Inf. Sci. & Eng., Australian Nat. Univ., Canberra, ACT, Australia
Abstract :
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 algorithm is accurate, fast, scalable and can be easily adjusted to search for a valid result within a specified time constraint. Our algorithm is particularly useful for real-time recognition of bar codes in portable hand-held devices with limited processing capability, such as mobile phones.
Keywords :
bar codes; image colour analysis; image recognition; image resolution; image restoration; bar code recognition; color saturation; defocusing; highly distorted images; low resolution images; mobile phones; nonuniform illumination; one dimensional bar code images; portable hand-held devices; substantial blurring; Colored noise; Decoding; Image recognition; Image resolution; Laser beams; Lenses; Lighting; Mobile handsets; Optical imaging; Pattern recognition; Bar codes; Feature extraction; Image segmentation; Pattern recognition; Peak Detection;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0727-3
DOI :
10.1109/ICASSP.2007.366013