Cantitate/Preț
Produs
Total produse
Vezi coșul
Image Copy-Move Forgery Detection de Badal Soni

Image Copy-Move Forgery Detection

Autor Badal Soni, Pradip K. Das
en Limba Engleză Hardback – 5 feb 2022
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.
Citește tot Restrânge

Preț: 92096 lei

Preț vechi: 112312 lei
-18%

Puncte Express: 1381
Paperback 84988 lei
Hardback 92096 lei

Carte tipărită la comandă

Livrare economică 09-23 decembrie

Livrare prin curier în România Termenul estimat este afișat lângă disponibilitate.
Transport gratuit pentru acest produs Plată online sau ramburs, în funcție de opțiunile comenzii.
Retur gratuit în 14 zile Comandă securizată și suport în română.
 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă

Specificații

ISBN-13: 9789811690402
ISBN-10: 9811690405
Pagini: 156
Ilustrații: XXI, 133 p. 66 illus., 60 illus. in color.
Dimensiuni: 160 x 241 x 15 mm
Greutate: 0.35 kg
Ediția:1st ed. 2022
Editura: Springer
Locul publicării:Singapore, Singapore

Cuprins

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.

Notă biografică

Nurul Amin Choudhury is a researcher in the field of artificial intelligence and wearable sensors. He holds a Ph.D. in Computer Science and Engineering from the National Institute of Technology (NIT) Silchar, where he previously served as a Senior Research Fellow and Junior Research Fellow in the Multimedia and Image Processing Lab under the Department of Computer Science and Engineering. He earned his M.Tech and B.Tech degrees from the National Institute of Technology, Meghalaya, and Jawaharlal Nehru Technological University, Hyderabad, in 2021 and 2018, respectively. His research interests include artificial intelligence, machine learning, IoT, AI-IoT in healthcare, human-computer interaction, feature engineering, and sensor-based human activity recognition, with a strong focus on real-world, uncontrolled environments and dataset development. Badal Soni is an Assistant Professor in the Department of Computer Engineering at the National Institute of Technology (NIT) Silchar, India. He completed his B.Tech at Rajiv Gandhi Technical University (formerly RGPV), Bhopal, and his M.Tech at the Indian Institute of Information Technology Design and Manufacturing (IIITDM), Jabalpur. Dr. Soni earned his Ph.D. from NIT Silchar. With over twelve years of teaching and research experience in computer science and information technology, he specializes in image processing, machine learning, and natural language processing. Dr. Soni has published over 95 papers in international journals and conference proceedings, authored two books, and edited five books. He is a senior member of IEEE and holds professional memberships in several organizations, including IEEE, ACM, IAENG, and IACSIT.

Textul de pe ultima copertă

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.

Caracteristici

Presents a detailed study of key points and block-based copy-move forgery detection techniques Aims at reducing the computational time without adversely affecting the efficiency of CMFD techniques Introduces a new ConvNet based image copy-move forgery detection process with source/target location