Cursive script text recognition in natural scence images : arabic text complexities / Saad Bin Ahmed, Muhammad Imran Razzak, Rubiyah Yusof.
Ahmed, Saad Bin.; Razzak, Muhammad Imran.; Rubiyah Yusof, 1961-
2020
TA1640
Available Online

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Title Cursive script text recognition in natural scence images : arabic text complexities / Saad Bin Ahmed, Muhammad Imran Razzak, Rubiyah Yusof.
Author Ahmed, Saad Bin.
ISBN 9789811512971 (electronic book)
9811512973 (electronic book)
9789811512964
9811512965
Publication Details Singapore : Springer, 2020.
Language English
Description 1 online resource
Call Number TA1640
Dewey Decimal Classification 006.4/24
Summary This book offers a broad and structured overview of the state-of-the-art methods that could be applied for context-dependent languages like Arabic. It also provides guidelines on how to deal with Arabic scene data that appeared in an uncontrolled environment impacted by different font size, font styles, image resolution, and opacity of text. Being an intrinsic script, Arabic and Arabic-like languages attract attention from research community. There are a number of challenges associated with the detection and recognition of Arabic text from natural images. This book discusses these challenges and open problems and also provides insights into the complexities and issues that researchers encounter in the context of Arabic or Arabic-like text recognition in natural and document images. It sheds light on fundamental questions, such as a) How the complexity of Arabic as a cursive scripts can be demonstrated b) What the structure of Arabic text is and how to consider the features from a given text and c) What guidelines should be followed to address the context learning ability of classifiers existing in machine learning.
Access Note Access limited to authorized users.
Added Author Razzak, Muhammad Imran.
Rubiyah Yusof, 1961-
Available in Other Form Print version: 9789811512964
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
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Foundations of Cursive Scene Text
Text in a wild and it's Challenges
3 Arabic Scene Text Acquisition and Statistics
Methods and Algorithm
Progress in Cursive Wild Text Recognition
Conclusion and Future Work.

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