A locally adaptive, diffusion based text binarization technique

B.A. Jacobs and E. Momoniat

Applied Mathematics and Computation, 2015, vol. 269, issue C, 464-472

Abstract: This research proposes an adaptive modification to a novel diffusion based text binarization technique. This technique uses linear diffusion with a nonlinear source term to achieve a binarizing effect. This simple isotropic process is compared to the state-of-the-art DIBCO contestants and produces remarkable results given the simplicity of the algorithm. Furthermore, the authors show how using a simple discretization scheme allows for the massively parallel implementation of this process.

Keywords: Binarization; Image denoising; Diffusion; Fitzhugh–Nagumo; Document image; GPGPU (search for similar items in EconPapers)
Date: 2015
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300315010139
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:269:y:2015:i:c:p:464-472

DOI: 10.1016/j.amc.2015.07.091

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().