Review on Local Binary Patterns Variants as Texture Descriptors for Copy-Move Forgery Detection

International Journal on Advanced Science, Engineering and Information Technology - Indonesia
doi 10.18517/ijaseit.7.5.3396
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Insight Society

Related search

Combining Cellular Automata and Local Binary Patterns for Copy-Move Forgery Detection

Multimedia Tools and Applications
Media TechnologyComputer NetworksHardwareCommunicationsArchitectureSoftware
2015English

Image Copy Move Forgery Detection: A Review

International Journal of Future Generation Communication and Networking
Computer NetworksCommunications
2018English

A Methodological Review on Copy-Move Forgery Detection for Image Forensics

International Journal of Digital Crime and Forensics
Software
2014English

Copy Move Image Forgery Detection Method Using Steerable Pyramid Transform and Texture Descriptor

2013English

Copy Move Image Forgery Detection Using Wavelet Transform

International Journal of Engineering Trends and Technology
2017English

Passive Approach for Copy-Move Forgery Detection for Digital Image

2017English

Copy Move Image Forgery Detection Based on Polar Fourier Representation

International Journal of Machine Learning and Computing
ManagementComputer Science ApplicationsInformation SystemsArtificial Intelligence
2018English

Local Binary Pattern Family Descriptors for Texture Classification

International Journal of Image, Graphics and Signal Processing
2018English

Improvement in Copy -Move Forgery Detection Using Hybrid Approach

International Journal of Modern Education and Computer Science
2016English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy