Parameter tuning for document image binarization using a racing algorithm

• It is investigated the use of I/F-Race to tune document image binarization methods.
• The method combines visual perception with the minimization of an energy function.
• Our experiments show that I/F-Race suggests promising parametric configurations.
• The binarization algorithm configured by I/F-Race outperforms other recent methods.

Binarization of images of old documents is considered a challenging task due to the wide diversity of degradation effects that can be found. To deal with this, many algorithms whose performance depends on an appropriate choice of their parameters have been proposed. In this work, it is investigated the application of a racing procedure based on a statistical approach, named I/F-Race, to suggest the parameters for two binarization algorithms reasoned (i) on the perception of objects by distance (POD) and (ii) on the POD combined with a Laplacian energy-based technique. Our experiments show that both algorithms had their performance statistically improved outperforming other recent binarization techniques. The second proposal presented herein ranked first in H-DIBCO (Handwritten Document Image Binarization Contest) 2014.