國立虎尾科技大學 |

Cognitively Inspired Video Text Processing

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Cognitively Inspired Video Text Processing/ by Palaiahnakote Shivakumara, Umapada Pal.
Author:	Shivakumara, Palaiahnakote.
other author:	Pal, Umapada.
Description:	X, 275 p. 151 illus., 113 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Optical data processing. -
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. - 1st ed. 2021. - X, 275 p. 151 illus., 113 illus. in color.online resource. - 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:

639187
Optical data processing.

LC Class. No.: TA1630-1650

Dewey Class. No.: 006.6

Cognitively Inspired Video Text Processing
LDR:02976nam a22004335i 4500 001 1057196
003 DE-He213
005 20211116053722.0
007 cr nn 008mamaa
008 220103s2021 si | s |||| 0|eng d
020 $a 9789811670695 $9 978-981-16-7069-5
024 7 $a 10.1007/978-981-16-7069-5 $2 doi
035 $a 978-981-16-7069-5
050 4 $a TA1630-1650
072 7 $a UYT $2 bicssc
072 7 $a COM012000 $2 bisacsh
072 7 $a UYT $2 thema
072 7 $a UYQV $2 thema
082 0 4 $a 006.6 $2 23
082 0 4 $a 006.37 $2 23
100 1 $a Shivakumara, Palaiahnakote. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1362614
245 1 0 $a Cognitively Inspired Video Text Processing $h [electronic resource] / $c by Palaiahnakote Shivakumara, Umapada Pal.
250 $a 1st ed. 2021.
264 1 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2021.
300 $a X, 275 p. 151 illus., 113 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Cognitive Intelligence and Robotics, $x 2520-1964
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.
650 0 $a Optical data processing. $3 639187
650 0 $a Signal processing. $3 561459
650 0 $a Image processing. $3 557495
650 0 $a Speech processing systems. $3 564428
650 1 4 $a Image Processing and Computer Vision. $3 670819
650 2 4 $a Signal, Image and Speech Processing. $3 670837
700 1 $a Pal, Umapada. $e editor. $1 https://orcid.org/0000-0002-5426-2618 $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1351815
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9789811670688
776 0 8 $i Printed edition: $z 9789811670701
776 0 8 $i Printed edition: $z 9789811670718
830 0 $a Cognitive Intelligence and Robotics, $x 2520-1956 $3 1279326
856 4 0 $u https://doi.org/10.1007/978-981-16-7069-5
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)