Thresholding of badly illuminated document images through photometric correction

ABSTRACT

This paper presents a document image thresholding technique that binarizes badly illuminated document images by the photometric correction. Based on the observation that illumination normally varies smoothly and document images often contain a uniformly colored background, the global shading variation is estimated by using a two-dimensional Savitzky-Golay filter that fits a least square polynomial surface to the luminance of a badly illuminated document image. With the knowledge of the global shading variation, shading degradation is then corrected through a compensation process that produces animage with roughly uniform illumination. Badly illuminated document images are accordingly binarized through the global thresholding of the compensated ones. Experiments show that the proposed thresholding technique is fast, robust, and efficient for the binarization of badly illuminated document images.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.6 Segmentation
          Subjects: Pixel classification

Additional Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.8 Scene Analysis
          Subjects: Photometry; Surface fitting
  I.7 DOCUMENT AND TEXT PROCESSING
      I.7.5 Document Capture
          Subjects: Optical character recognition (OCR); Document analysis

General Terms:
Algorithms, Design, Experimentation

Keywords:
badly-illuminated document images, document image analysis, document image thresholding