Skip to Main Content (Press Enter)

Logo CNR
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills

UNI-FIND
Logo CNR

|

UNI-FIND

cnr.it
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills
  1. Outputs

An Adaptive Copy-Move Forgery Detection Using Wavelet Coefficients Multiscale Decay

Chapter
Publication Date:
2019
abstract:
In this paper, an adaptive method for copy-move forgery detection and localization in digital images is proposed. The method employs wavelet transform with non constant Q factor and characterizes image pixels through the multiscale behavior of corresponding wavelet coefficients. The detection of forged regions is then performed by considering similar those pixels having the same multiscale behavior. The method is pointwise and the length of pixel features vector is image dependent, allowing for a more precise and fast detection of forged regions. The qualitative and quantitative evaluation of the experimental results reveals that the proposed method outperforms some existing transform-based methods in terms of performance and execution time.
Iris type:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
Image Forensics; Copy-move forgery detection; Wavelet transform; Lipschitz exponents
List of contributors:
Bruni, Vittoria; Ramella, Giuliana; Vitulano, Domenico
Authors of the University:
RAMELLA GIULIANA
Handle:
https://iris.cnr.it/handle/20.500.14243/367959
Book title:
Computer Analysis of Images and Patterns
  • Overview

Overview

URL

http://www.scopus.com/record/display.url?eid=2-s2.0-85072851157&origin=inward
  • Use of cookies

Powered by VIVO | Designed by Cineca | 26.5.0.0 | Sorgente dati: PREPROD (Ribaltamento disabilitato)