.png){kind=icon}
Return
A locally adaptive, diffusion based text binarization technique
.png){kind=icon}
PRE
AI
DOI：10.1016/j.amc.2015.07.091.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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. (C) 2015 Elsevier Inc. All rights reserved.
Keywords:
Binarization
Image denoising
Diffusion
Fitzhugh-Nagumo
Document image
GPGPU
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.4
Papers:
2.3W
Citations:
3.3W
Organization
Cited Papers
.png){kind=icon}
ShareSave
ShareSaveShareSave
View more