Bhowmik | Document Layout Analysis | Buch | 978-981-99-4276-3 | sack.de

Buch, Englisch, 86 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 160 g

Reihe: SpringerBriefs in Computer Science

Bhowmik

Document Layout Analysis


1. Auflage 2023
ISBN: 978-981-99-4276-3
Verlag: Springer Nature Singapore

Buch, Englisch, 86 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 160 g

Reihe: SpringerBriefs in Computer Science

ISBN: 978-981-99-4276-3
Verlag: Springer Nature Singapore


Document layout analysis (DLA) is a crucial step towards the development of an effective document image processing system. In the early days of document image processing, DLA was not considered as a complete and complex research problem, rather just a pre-processing step having some minor challenges. The main reason for that is the type of layout being considered for processing was simple. Researchers started paying attention to this complex problem as they come across a large variety of documents. This book presents a clear view of the past, present, and future of DLA, and it also discusses two recent methods developed to address the said problem.


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Research


Autoren/Hrsg.


Weitere Infos & Material


Chapter 1. Introduction.-  Chapter 2. Binarization.- Chapter 3. Document Region Segmentation.- Chapter 4. Document Region Classification.-  Chapter 5. Case Study.- Chapter 6. Summary.



Dr. Showmik Bhowmik is currently working as an assistant professor in the Department of Computer Science and Engineering at Ghani Khan Choudhury Institute of Engineering and Technology, a centrally funded technical institute under the Ministry of Education, Government of India. He has received his ME and PhD degree from Jadavpur University, India, from the Department of Computer Science and Engineering. During his PhD, Dr. Bhowmik was selected as Visvesvaraya Research Fellow under the Ministry of Electronics and Information Technology, Government of India. Dr. Bhowmik has more than 34 publications in SCI-indexed journals and conferences. His current areas of research are pattern recognition, image processing, offline handwriting recognition, machine learning, and deep learning.



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