Image Copy-Move Forgery Detection using Color Features and Hierarchical Feature Point Matching

Yi-Lin Tsai, Jin-Jang Leou

2021

Abstract

In this study, an image copy-move forgery detection approach using color features and hierarchical feature point matching is proposed. The proposed approach contains three main stages, namely, pre-processing and feature extraction, hierarchical feature point matching, and iterative forgery localization and post-processing. In the proposed approach, Gaussian-blurred images and difference of Gaussians (DoG) images are constructed. Hierarchical feature point matching is employed to find matched feature point pairs, in which two matching strategies, namely, group matching via scale clustering and group matching via overlapped gray level clustering, are used. Based on the experimental results obtained in this study, the performance of the proposed approach is better than those of three comparison approaches.

Paper Citation

in Harvard Style

Tsai Y. and Leou J. (2021). Image Copy-Move Forgery Detection using Color Features and Hierarchical Feature Point Matching. In Proceedings of the International Conference on Image Processing and Vision Engineering - Volume 1: IMPROVE, ISBN 978-989-758-511-1, pages 153-159. DOI: 10.5220/0010492301530159

in Bibtex Style

@conference{improve21,
author={Yi-Lin Tsai and Jin-Jang Leou},
title={Image Copy-Move Forgery Detection using Color Features and Hierarchical Feature Point Matching},
booktitle={Proceedings of the International Conference on Image Processing and Vision Engineering - Volume 1: IMPROVE,},
year={2021},
pages={153-159},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010492301530159},
isbn={978-989-758-511-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Image Processing and Vision Engineering - Volume 1: IMPROVE,
TI - Image Copy-Move Forgery Detection using Color Features and Hierarchical Feature Point Matching
SN - 978-989-758-511-1
AU - Tsai Y.
AU - Leou J.
PY - 2021
SP - 153
EP - 159
DO - 10.5220/0010492301530159