The Indexing and Retrieval of Document Images: A Survey

Author(s):  
David Doermann
2016 ◽  
Vol 11 (12) ◽  
pp. 1187 ◽  
Author(s):  
Hassan El Bahi ◽  
Abdelkarim Zatni
Keyword(s):  

1997 ◽  
Author(s):  
Omid Kia ◽  
David Doermann ◽  
Azriel Rosenfled ◽  
Rama Chellappa
Keyword(s):  

1996 ◽  
Author(s):  
Vikrant Kobla ◽  
David Doermann ◽  
King-Ip Lin ◽  
Christos Faloutsos

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Wei Xiong ◽  
Lei Zhou ◽  
Ling Yue ◽  
Lirong Li ◽  
Song Wang

AbstractBinarization plays an important role in document analysis and recognition (DAR) systems. In this paper, we present our winning algorithm in ICFHR 2018 competition on handwritten document image binarization (H-DIBCO 2018), which is based on background estimation and energy minimization. First, we adopt mathematical morphological operations to estimate and compensate the document background. It uses a disk-shaped structuring element, whose radius is computed by the minimum entropy-based stroke width transform (SWT). Second, we perform Laplacian energy-based segmentation on the compensated document images. Finally, we implement post-processing to preserve text stroke connectivity and eliminate isolated noise. Experimental results indicate that the proposed method outperforms other state-of-the-art techniques on several public available benchmark datasets.


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