Effective document image binarization via a convex variational level set model

作者：

Highlights：

• We propose a strict convex variational level set model for document binarization, and it has a unique global minimizer.

• It is an initialization-flexible model, and the evolution termination condition can be set via level set function.

• Our model can deal with many kinds of degradations, such as, low contrast, bleed-through, faint characters, texture.

• Our model can achieve comparable or better performance. Moreover, it is efficient and robust to noise to some extent.

摘要

•We propose a strict convex variational level set model for document binarization, and it has a unique global minimizer.•It is an initialization-flexible model, and the evolution termination condition can be set via level set function.•Our model can deal with many kinds of degradations, such as, low contrast, bleed-through, faint characters, texture.•Our model can achieve comparable or better performance. Moreover, it is efficient and robust to noise to some extent.

论文关键词：Document image binarization,Convex variational model,Level set,Initialization

论文评审过程：Received 17 March 2021, Revised 21 October 2021, Accepted 6 December 2021, Available online 20 December 2021, Version of Record 20 December 2021.

论文官网地址：https://doi.org/10.1016/j.amc.2021.126861