Image Copy-Move Forgery Detection

New Tools and Techniques

Inbunden, Engelska, 2022

Av Badal Soni, Pradip K. Das

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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. Five different image copy-move forgery detection techniques are implemented to overcome the limitations of existing copy-move forgery detection techniques.

Produktinformation

Utgivningsdatum2022-02-05
Mått155 x 235 x 15 mm
Vikt407 g
FormatInbunden
SpråkEngelska
SerieStudies in Computational Intelligence
Antal sidor133
FörlagSpringer Verlag, Singapore
ISBN9789811690402

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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 hisM.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.

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.