Technology of Information Security
|
App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 9
2838-2844

Copy-move forgery detection based on improved saliency map and local feature matching

Zhao Hongtu
Zhou Qiuhao
School of Physical & Electronic Information, Henan Polytechnic University, Jiaozuo Henan 454003, China
DOI: 10.19734/j.issn.1001-3695.2023.01.0012

Abstract

The method of detecting the whole tampered image increases many unnecessary calculations. In order to reduce the computational complexity and further improve the detection accuracy, this paper proposed a copy-move forgery detection method based on improved saliency map and local feature matching. Firstly, it combined the gradient of image to improve the saliency map, and separated the local salient regions containing high texture information of the image. Secondly, it only used SIFT(scale invariant feature transform) algorithm to extract feature points in this local area. Then, it adopted density clustering and two-stage matching strategy for images with low saliency, and adopted the strategy of superpixel segmentation and salient block feature matching for images with high saliency. Finally, it combined PSNR and morphological operations to locate the tampered area. Experiments on two public datasets show that the average detection time of this method is less than 10 s, and the average detection accuracy is greater than 97%, which are better than the compared methods. The experimental results show that this method can greatly reduce the detection time, effectively improve the detection accuracy, and has good robustness to geometric transformation and post-processing operations.

Foundation Support

河南省科技厅科技攻关和软科学项目(192102310446)
河南省高校基本科研业务费专项资金资助项目(NSFRF210406)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.01.0012
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 9
Section: Technology of Information Security
Pages: 2838-2844
Serial Number: 1001-3695(2023)09-044-2838-07

Publish History

[2023-03-16] Accepted Paper
[2023-09-05] Printed Article

Cite This Article

赵鸿图, 周秋豪. 基于改进显著图和局部特征匹配的copy-move窜改检测 [J]. 计算机应用研究, 2023, 40 (9): 2838-2844. (Zhao Hongtu, Zhou Qiuhao. Copy-move forgery detection based on improved saliency map and local feature matching [J]. Application Research of Computers, 2023, 40 (9): 2838-2844. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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