Document page classification algorithms in low-end copy pipeline

Xiaogang Dong; Kai-Lung Hua; Peter Majewicz; Gordon McNutt; Charles A. Bouman; Jan P. Allebach; Ilya Pollak

doi:10.1117/1.3010879

1 October 2008 Document page classification algorithms in low-end copy pipeline

Xiaogang Dong, Kai-Lung Hua, Peter Majewicz, Gordon McNutt, Charles A. Bouman, Jan P. Allebach, Ilya Pollak

Author Affiliations +

Journal of Electronic Imaging, Vol. 17, Issue 4, 043011 (October 2008). https://doi.org/10.1117/1.3010879

Abstract

We develop real-time, low-complexity image classification algorithms suitable for a copy mode selector embedded in a low-end copier. The algorithms classify scanned images represented in RGB or in an opponent color space. Classes are the eight combinations of mono/color and text/mix/picture/photo. Classification is 30–98% accurate with misclassifications tending to be benign. The algorithms provide for improved copy quality, a simplified user interface, and increased copy rate.

©(2008) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Xiaogang Dong, Kai-Lung Hua, Peter Majewicz, Gordon McNutt, Charles A. Bouman, Jan P. Allebach, and Ilya Pollak "Document page classification algorithms in low-end copy pipeline," Journal of Electronic Imaging 17(4), 043011 (1 October 2008). https://doi.org/10.1117/1.3010879

Published: 1 October 2008

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