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Cognitively inspired video text proc...

Shivakumara, Palaiahnakote.

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Cognitively inspired video text processing

Record Type:	Electronic resources : Monograph/item
Title/Author:	Cognitively inspired video text processing/ by Palaiahnakote Shivakumara, Umapada Pal.
Author:	Shivakumara, Palaiahnakote.
other author:	Pal, Umapada.
Published:	Singapore :Springer Singapore : : 2021.,
Description:	x, 275 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Chapter 1. Introduction -- Chapter 2. Key Text Frame Selection from Video -- Chapter 3. Text and Non-Text Frame Classification in Video -- Chapter 4. Text Detection in Video -- Chapter 5. Text Detection in Images -- Chapter 6. Word and Character Segmentation -- Chapter 7. Video Text Type Classification -- Chapter 8. Video Text Enhancement for Recognition -- Chapter 9. Video Text Recognition -- Chapter 10. Conclusion and Future Directions.
Contained By:	Springer Nature eBook
Subject:	Text processing (Computer science) -
Online resource:	https://doi.org/10.1007/978-981-16-7069-5
ISBN:	9789811670695

Cognitively inspired video text processing
Shivakumara, Palaiahnakote.

Cognitively inspired video text processing[electronic resource] /by Palaiahnakote Shivakumara, Umapada Pal. - Singapore :Springer Singapore :2021. - x, 275 p. :ill. (some col.), digital ;24 cm. - Cognitive intelligence and robotics,2520-1964. - Cognitive intelligence and robotics..

Chapter 1. Introduction -- Chapter 2. Key Text Frame Selection from Video -- Chapter 3. Text and Non-Text Frame Classification in Video -- Chapter 4. Text Detection in Video -- Chapter 5. Text Detection in Images -- Chapter 6. Word and Character Segmentation -- Chapter 7. Video Text Type Classification -- Chapter 8. Video Text Enhancement for Recognition -- Chapter 9. Video Text Recognition -- Chapter 10. Conclusion and Future Directions.

As technologies are fast advancing, the importance of text detection and recognition is receiving special attention from the researchers. Thus, one can see several real-time applications of video text processing which requires cognitive-based methods to find a solution. The main applications are (1) retrieving and indexing video based on semantic of the content of the video, (2) machine translation to assist foreigners, (3) assisting blind people to walk on the road freely without aid, (4) automatic vehicle driving, (5) license plate tracing to catch vehicles which violate the traffic signals, (6) monitoring the images posted on social media based on text and content of the images, (7) identifying the location based on the address of the street and shops, etc., (8) tracing players in the sports based on the jersey/bib number or text, and (9) in the same way, tracing the bib number in case of marathon and other events. For the above-mentioned applications, text detection and recognition in video and natural scene images is an integral part of the system.

ISBN: 9789811670695

Standard No.: 10.1007/978-981-16-7069-5doiSubjects--Topical Terms:

532552
Text processing (Computer science)

LC Class. No.: QA76.9.T48 / S45 2021

Dewey Class. No.: 006.37

Cognitively inspired video text processing
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505 0 $a Chapter 1. Introduction -- Chapter 2. Key Text Frame Selection from Video -- Chapter 3. Text and Non-Text Frame Classification in Video -- Chapter 4. Text Detection in Video -- Chapter 5. Text Detection in Images -- Chapter 6. Word and Character Segmentation -- Chapter 7. Video Text Type Classification -- Chapter 8. Video Text Enhancement for Recognition -- Chapter 9. Video Text Recognition -- Chapter 10. Conclusion and Future Directions.
520 $a As technologies are fast advancing, the importance of text detection and recognition is receiving special attention from the researchers. Thus, one can see several real-time applications of video text processing which requires cognitive-based methods to find a solution. The main applications are (1) retrieving and indexing video based on semantic of the content of the video, (2) machine translation to assist foreigners, (3) assisting blind people to walk on the road freely without aid, (4) automatic vehicle driving, (5) license plate tracing to catch vehicles which violate the traffic signals, (6) monitoring the images posted on social media based on text and content of the images, (7) identifying the location based on the address of the street and shops, etc., (8) tracing players in the sports based on the jersey/bib number or text, and (9) in the same way, tracing the bib number in case of marathon and other events. For the above-mentioned applications, text detection and recognition in video and natural scene images is an integral part of the system.
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