國立虎尾科技大學 |

Image Copy-Move Forgery Detection = New Tools and Techniques /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Image Copy-Move Forgery Detection / by Badal Soni, Pradip K. Das.
Reminder of title:	New Tools and Techniques /
Author:	Soni, Badal.
other author:	Das, Pradip K.
Description:	XXI, 133 p. 66 illus., 60 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Signal processing. -
Online resource:	https://doi.org/10.1007/978-981-16-9041-9
ISBN:	9789811690419

Image Copy-Move Forgery Detection = New Tools and Techniques /
Soni, Badal.

Image Copy-Move Forgery Detection New Tools and Techniques /[electronic resource] :by Badal Soni, Pradip K. Das. - 1st ed. 2022. - XXI, 133 p. 66 illus., 60 illus. in color.online resource. - Studies in Computational Intelligence,10171860-9503 ;. - Studies in Computational Intelligence,564.

Introduction -- Background Study and Analysis -- Copy-Move Forgery Detection using Local Binary Pattern Histogram Fourier Features -- Blur Invariant Block-based CMFD System using FWHT Features -- Geometric Transformation Invariant Improved Block based Copy-Move Forgery Detection -- Key-points based Enhanced Copy-Move Forgery Detection System using DBSCAN Clustering Algorithm -- Image Copy-Move Forgery Detection using Deep Convolutional Neural Networks.

This book presents a detailed study of key points and block-based copy-move forgery detection techniques with a critical discussion about their pros and cons. It also highlights the directions for further development in image forgery detection. The book includes various publicly available standard image copy-move forgery datasets that are experimentally analyzed and presented with complete descriptions. Five different image copy-move forgery detection techniques are implemented to overcome the limitations of existing copy-move forgery detection techniques. The key focus of work is to reduce the computational time without adversely affecting the efficiency of these techniques. In addition, these techniques are also robust to geometric transformation attacks like rotation, scaling, or both.

ISBN: 9789811690419

Standard No.: 10.1007/978-981-16-9041-9doiSubjects--Topical Terms:

561459
Signal processing.

LC Class. No.: TK5102.9

Dewey Class. No.: 621.3822

Image Copy-Move Forgery Detection = New Tools and Techniques /
LDR:02733nam a22004335i 4500 001 1093981
003 DE-He213
005 20220429034947.0
007 cr nn 008mamaa
008 221228s2022 si | s |||| 0|eng d
020 $a 9789811690419 $9 978-981-16-9041-9
024 7 $a 10.1007/978-981-16-9041-9 $2 doi
035 $a 978-981-16-9041-9
050 4 $a TK5102.9
072 7 $a TJF $2 bicssc
072 7 $a UYS $2 bicssc
072 7 $a TEC008000 $2 bisacsh
072 7 $a TJF $2 thema
072 7 $a UYS $2 thema
082 0 4 $a 621.3822 $2 23
100 1 $a Soni, Badal. $e editor. $1 https://orcid.org/0000-0002-9617-9468 $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1313510
245 1 0 $a Image Copy-Move Forgery Detection $h [electronic resource] : $b New Tools and Techniques / $c by Badal Soni, Pradip K. Das.
250 $a 1st ed. 2022.
264 1 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2022.
300 $a XXI, 133 p. 66 illus., 60 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 Studies in Computational Intelligence, $x 1860-9503 ; $v 1017
505 0 $a Introduction -- Background Study and Analysis -- Copy-Move Forgery Detection using Local Binary Pattern Histogram Fourier Features -- Blur Invariant Block-based CMFD System using FWHT Features -- Geometric Transformation Invariant Improved Block based Copy-Move Forgery Detection -- Key-points based Enhanced Copy-Move Forgery Detection System using DBSCAN Clustering Algorithm -- Image Copy-Move Forgery Detection using Deep Convolutional Neural Networks.
520 $a This book presents a detailed study of key points and block-based copy-move forgery detection techniques with a critical discussion about their pros and cons. It also highlights the directions for further development in image forgery detection. The book includes various publicly available standard image copy-move forgery datasets that are experimentally analyzed and presented with complete descriptions. Five different image copy-move forgery detection techniques are implemented to overcome the limitations of existing copy-move forgery detection techniques. The key focus of work is to reduce the computational time without adversely affecting the efficiency of these techniques. In addition, these techniques are also robust to geometric transformation attacks like rotation, scaling, or both.
650 0 $a Signal processing. $3 561459
650 0 $a Computer vision. $3 561800
650 0 $a Computational intelligence. $3 568984
650 1 4 $a Digital and Analog Signal Processing. $3 1366690
650 2 4 $a Computer Vision. $3 1127422
650 2 4 $a Computational Intelligence. $3 768837
700 1 $a Das, Pradip K. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1402007
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9789811690402
776 0 8 $i Printed edition: $z 9789811690426
776 0 8 $i Printed edition: $z 9789811690433
830 0 $a Studies in Computational Intelligence, $x 1860-949X ; $v 564 $3 1253640
856 4 0 $u https://doi.org/10.1007/978-981-16-9041-9
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)