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Kategorie szczegółowe BISAC

Image Copy-Move Forgery Detection: New Tools and Techniques

ISBN-13: 9789811690402 / Angielski / Twarda / 2022 / 156 str.

Badal Soni;Pradip K. Das
Image Copy-Move Forgery Detection: New Tools and Techniques Soni, Badal 9789811690402 Springer Singapore - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Image Copy-Move Forgery Detection: New Tools and Techniques

ISBN-13: 9789811690402 / Angielski / Twarda / 2022 / 156 str.

Badal Soni;Pradip K. Das
cena 564,88 zł
(netto: 537,98 VAT:  5%)

Najniższa cena z 30 dni: 539,74 zł
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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.

Kategorie:
Technologie
Kategorie BISAC:
Technology & Engineering > Electronics - General
Computers > Software Development & Engineering - Computer Graphics
Technology & Engineering > Engineering (General)
Wydawca:
Springer Singapore
Seria wydawnicza:
Studies in Computational Intelligence
Język:
Angielski
ISBN-13:
9789811690402
Rok wydania:
2022
Ilość stron:
156
Waga:
0.40 kg
Wymiary:
23.39 x 15.6 x 1.12
Oprawa:
Twarda
Wolumenów:
01
Dodatkowe informacje:
Wydanie ilustrowane

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.

Badal Soni is an Assistant Professor at the Department of Computer Engineering, National Institute of Technology (NIT) Silchar, India. He completed his B. Tech. from Rajiv Gandhi Technical University (formerly RGPV) Bhopal, India, and M. Tech. from Indian Institute of Information Technology (IIITDM) Jabalpur, India. He received his Ph.D. from NIT Silchar, India. Dr. Soni has teaching and research experience of over seven years in computer science and information technology with a special interest in computer graphics, image processing, speech, and language processing. He has published over 35 papers in international journals and conference proceedings. He is the Senior member of IEEE and professional members of various bodies like IEEE, ACM, IAENG & IACSIT.

Pradip K. Das is a Professor at the Department of Computer Science and Engineering, Indian Institute of Technology Guwahati, India. Prof. Das completed his B.Sc. Statistics (Hons.) from Gauhati University in 1989. He got his M.Sc. Mathematical Statistics and Ph.D. degrees from Delhi University, in 1991 and 1999, respectively. Prof. Das has successfully guided 5 students for their Ph.D. theses and he is presently supervising 5 Ph.D. scholars. Prof. Das has got several publications to his credit. His research areas are speech & language processing, mobile robotics, IoT & cyber-physical systems, software engineering, algorithms, and smart devices.

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.



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