26 February 2015 Correcting geometric and photometric distortion of document images on a smartphone
Author Affiliations +
J. of Electronic Imaging, 24(1), 013038 (2015). doi:10.1117/1.JEI.24.1.013038
A set of document image processing algorithms for improving the optical character recognition (OCR) capability of smartphone applications is presented. The scope of the problem covers the geometric and photometric distortion correction of document images. The proposed framework was developed to satisfy industrial requirements. It is implemented on an off-the-shelf smartphone with limited resources in terms of speed and memory. Geometric distortions, i.e., skew and perspective distortion, are corrected by sending horizontal and vertical vanishing points toward infinity in a downsampled image. Photometric distortion includes image degradation from moiré pattern noise and specular highlights. Moiré pattern noise is removed using low-pass filters with different sizes independently applied to the background and text region. The contrast of the text in a specular highlighted area is enhanced by locally enlarging the intensity difference between the background and text while the noise is suppressed. Intensive experiments indicate that the proposed methods show a consistent and robust performance on a smartphone with a runtime of less than 1 s.
© 2015 SPIE and IS&T
Christian Simon, Williem, In Kyu Park, "Correcting geometric and photometric distortion of document images on a smartphone," Journal of Electronic Imaging 24(1), 013038 (26 February 2015). https://doi.org/10.1117/1.JEI.24.1.013038


Optical character recognition

Image processing

Binary data

Image filtering

Image resolution



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