Digital Image Forensics - Theory and Implementation (Hardcover, 1st ed. 2020)

This book discusses blind investigation and recovery of digital evidence left behind on digital devices, primarily for the purpose of tracing cybercrime sources and criminals. It presents an overview of the challenges of digital image forensics, with a specific focus on two of the most common forensic problems. The first part of the book addresses image source investigation, which involves mapping an image back to its camera source to facilitate investigating and tracing the source of a crime. The second part of the book focuses on image-forgery detection, primarily focusing on "copy-move forgery" in digital images, and presenting effective solutions to copy-move forgery detection with an emphasis on additional related challenges such as blur-invariance, similar genuine object identification, etc. The book concludes with future research directions, including counter forensics. With the necessary mathematical information in every chapter, the book serves as a useful reference resource for researchers and professionals alike. In addition, it can also be used as a supplementary text for upper-undergraduate and graduate-level courses on "Digital Image Processing", "Information Security", "Machine Learning", "Computer Vision" and "Multimedia Security and Forensics".

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Studies in Computational Intelligence, 755
Release date:	May 2019
First published:	2020
Authors:	Aniket Roy • Rahul Dixit • Ruchira Naskar • Rajat Subhra Chakraborty
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	89
Edition:	1st ed. 2020
ISBN-13:	978-981-10-7643-5
Categories:	Books > Social sciences > Sociology, social studies > Crime & criminology > General Books > Computing & IT > Applications of computing > Image processing > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General Promotions
LSN:	981-10-7643-X
Barcode:	9789811076435

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