4.6 Article

Fake region identification in an image using deep learning segmentation model

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Mathematical & Computational Biology

Efficient Approach towards Detection and Identification of Copy Move and Image Splicing Forgeries Using Mask R-CNN with MobileNet V1

Kalyani Dhananjay Kadam et al.

Summary: With the availability of image editing tools and online platforms, manipulated images have become widely distributed, impacting society and misleading decision-making processes. The need for effective methods to detect and identify forgeries has led to the development of various techniques, including traditional handcrafted features and deep learning networks. However, deep learning networks can be expensive in terms of parameters and computational cost. This research introduces a lightweight model, Mask R-CNN with MobileNet, which outperforms existing models in detecting copy move and image splicing forgeries.

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE (2022)

Article Computer Science, Artificial Intelligence

Detection of Copy-Move Forgery in Digital Image Using Multi-scale, Multi-stage Deep Learning Model

Ankit Kumar Jaiswal et al.

Summary: This paper presents a deep learning CNN model for copy-move forgery (CMF) detection, which improves accuracy and efficiency through multi-scale input and multi-stage convolutional layer design. The model is validated on two different publicly available datasets and compared with state-of-the-art methods, showing that the proposed data-driven approach performs better.

NEURAL PROCESSING LETTERS (2022)

Article Computer Science, Information Systems

An Efficient CNN Model to Detect Copy-Move Image Forgery

Khalid M. Hosny et al.

Summary: This paper proposes an accurate convolutional neural network (CNN) architecture for detecting copy-move image forgery. The proposed architecture is computationally lightweight and includes a suitable number of convolutional and max-pooling layers. Additionally, a fast and accurate testing process is presented, with a testing time of 0.83 seconds. Empirical experiments on benchmark datasets demonstrate the efficiency of the proposed model, achieving 100% accuracy.

IEEE ACCESS (2022)

Article Computer Science, Information Systems

A Serial Image Copy-Move Forgery Localization Scheme With Source/Target Distinguishment

Beijing Chen et al.

Summary: This paper improves the parallel deep neural network scheme BusterNet for image copy-move forgery localization with source/target region distinguishment. The proposed algorithm outperforms the state-of-the-art algorithms in terms of similarity detection ability and source/target distinguishment ability on four publicly available datasets.

IEEE TRANSACTIONS ON MULTIMEDIA (2021)

Article Computer Science, Artificial Intelligence

Forensic image analysis using inconsistent noise pattern

Ankit Kumar Jaiswal et al.

Summary: With the advancement of image acquisition devices and social networking services, the importance of verifying image authenticity has become increasingly prominent. Currently, techniques based on noise inconsistency have become an important method for detecting false images.

PATTERN ANALYSIS AND APPLICATIONS (2021)

Article Computer Science, Theory & Methods

Noiseprint: A CNN-Based Camera Model Fingerprint

Davide Cozzolino et al.

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2020)

Article Computer Science, Artificial Intelligence

Copy-for-duplication forgery detection in colour images using QPCETMs and sub-image approach

Khalid M. Hosny et al.

IET IMAGE PROCESSING (2019)

Article Computer Science, Artificial Intelligence

Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries

Jawadul H. Bappy et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2019)

Proceedings Paper Imaging Science & Photographic Technology

RESIDUAL U-NET FOR RETINAL VESSEL SEGMENTATION

Di Li et al.

2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) (2019)

Article Imaging Science & Photographic Technology

Copy-move forgery detection of duplicated objects using accurate PCET moments and Morphological operators

Khalid M. Hosny et al.

IMAGING SCIENCE JOURNAL (2018)

Article Computer Science, Information Systems

Content-aware detection of JPEG grid inconsistencies for intuitive image forensics

Chryssanthi Iakovidou et al.

JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION (2018)

Article Computer Science, Information Systems

A Markov based image forgery detection approach by analyzing CFA artifacts

Amneet Singh et al.

MULTIMEDIA TOOLS AND APPLICATIONS (2018)

Article Engineering, Electrical & Electronic

Blind image splicing detection via noise level function

Nan Zhu et al.

SIGNAL PROCESSING-IMAGE COMMUNICATION (2018)

Article Computer Science, Information Systems

Image splicing localization using PCA-based noise level estimation

Hui Zeng et al.

MULTIMEDIA TOOLS AND APPLICATIONS (2017)

Article Computer Science, Information Systems

Handling multiple materials for exposure of digital forgeries using 2-D lighting environments

Christian Riess et al.

MULTIMEDIA TOOLS AND APPLICATIONS (2017)

Article Computer Science, Artificial Intelligence

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Vijay Badrinarayanan et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2017)

Article Computer Science, Artificial Intelligence

Multi-Scale Fusion for Improved Localization of Malicious Tampering in Digital Images

Pawel Korus et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2016)

Article Computer Science, Theory & Methods

A Bayesian-MRF Approach for PRNU-Based Image Forgery Detection

Giovanni Chierchia et al.

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2014)

Article Computer Science, Artificial Intelligence

Exposing Region Splicing Forgeries with Blind Local Noise Estimation

Siwei Lyu et al.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2014)

Article Computer Science, Artificial Intelligence

Image forgery detection using steerable pyramid transform and local binary pattern

Ghulam Muhammad et al.

MACHINE VISION AND APPLICATIONS (2014)

Article Computer Science, Theory & Methods

Exposing Digital Image Forgeries by Illumination Color Classification

Tiago Jose de Carvalho et al.

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2013)

Article Engineering, Electrical & Electronic

Detecting Image Forgery Using Perspective Constraints

Heng Yao et al.

IEEE SIGNAL PROCESSING LETTERS (2012)

Article Computer Science, Theory & Methods

Image Forgery Localization via Fine-Grained Analysis of CFA Artifacts

Pasquale Ferrara et al.

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2012)

Article Computer Science, Artificial Intelligence

Digital image splicing detection based on Markov features in DCT and DWT domain

Zhongwei He et al.

PATTERN RECOGNITION (2012)

Article Computer Science, Theory & Methods

Identifying Image Composites Through Shadow Matte Consistency

Qiguang Liu et al.

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2011)

Article Computer Science, Theory & Methods

Detecting and Extracting the Photo Composites Using Planar Homography and Graph Cut

Wei Zhang et al.

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2010)

Article Computer Science, Artificial Intelligence

Using noise inconsistencies for blind image forensics

Babak Mahdian et al.

IMAGE AND VISION COMPUTING (2009)

Article Engineering, Electrical & Electronic

Passive detection of doctored JPEG image via block artifact grid extraction

Weihai Li et al.

SIGNAL PROCESSING (2009)

Article Computer Science, Theory & Methods

Exposing digital forgeries in complex lighting environments

Micah K. Johnson et al.

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2007)

Article Computer Science, Theory & Methods

Nonintrusive component forensics of visual sensors using output images

Ashwin Swaminathan et al.

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2007)