Text Localization in Historical Document Images with Local Binary Patterns and Variance Models-Reference-Cited by-同舟云学术

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Text Localization in Historical Document Images with Local Binary Patterns and Variance Models

Published:2013 Issue: Volume: Page:501-508
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Bhowmik Tapan Kumar,Kar Manika

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-45062-4_69

Reference12 articles.

1. Biblioteca Nacional De Portugal, http://purl.pt/index/geral/PT/index.html

2. Baird, H.: Digital libraries and document image analysis. In: Proc. of the 7th ICDAR, pp. 2–14 (2003)

3. Etemad, K., Doermann, D., Chellappa, R.: Multiscale segmentation of unstructured document pages using soft decision integration. Trans. on. IEEE 19(1), 92–96 (1997)

4. Fletcher, L.A., Kasturi, R.: A robust algorithm for text string separation from mixed text/graphics images. Trans. on. IEEE 10(6), 910–918 (1988)

5. Gorman, L.O.: The document spectrum for page layout analysis. Trans. on. IEEE 15(11), 1162–1173 (1993)

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Historical Document Image Segmentation Combining Deep Learning and Gabor Features;Lecture Notes in Computer Science;2023

2. Texture feature benchmarking and evaluation for historical document image analysis;International Journal on Document Analysis and Recognition (IJDAR);2017-01-05

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