DeepOtsu: Document enhancement and binarization using iterative deep learning
作者：
Highlights：
• We propose a novel iteration deep learning which can improve the input image iteratively.
• We apply the proposed iterative deep learning for document enhancement and binarization in two possible ways: recurrent refinement and stacked refinement.
• Our proposed method provides a new, clean version of the degraded image, one that is suitable for visualization and which shows promising results for binarization using Otsu’s global threshold.
摘要
•We propose a novel iteration deep learning which can improve the input image iteratively.•We apply the proposed iterative deep learning for document enhancement and binarization in two possible ways: recurrent refinement and stacked refinement.•Our proposed method provides a new, clean version of the degraded image, one that is suitable for visualization and which shows promising results for binarization using Otsu’s global threshold.
论文关键词：Document enhancement and binarization,Convolutional neural networks,Iterative deep learning,Recurrent refinement
论文评审过程：Received 15 August 2018, Revised 6 December 2018, Accepted 13 January 2019, Available online 25 January 2019, Version of Record 27 March 2019.
论文官网地址：https://doi.org/10.1016/j.patcog.2019.01.025
