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22 September 2015 Optical character recognition of camera-captured images based on phase features
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Abstract
Nowadays most of digital information is obtained using mobile devices specially smartphones. In particular, it brings the opportunity for optical character recognition in camera-captured images. For this reason many recognition applications have been recently developed such as recognition of license plates, business cards, receipts and street signal; document classification, augmented reality, language translator and so on. Camera-captured images are usually affected by geometric distortions, nonuniform illumination, shadow, noise, which make difficult the recognition task with existing systems. It is well known that the Fourier phase contains a lot of important information regardless of the Fourier magnitude. So, in this work we propose a phase-based recognition system exploiting phase-congruency features for illumination/scale invariance. The performance of the proposed system is tested in terms of miss classifications and false alarms with the help of computer simulation.
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Julia Diaz-Escobar and Vitaly Kober "Optical character recognition of camera-captured images based on phase features", Proc. SPIE 9599, Applications of Digital Image Processing XXXVIII, 959903 (22 September 2015); https://doi.org/10.1117/12.2188330
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