A locally adaptive, diffusion based text binarization technique

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.