An Enhanced Hybrid Method based on Local and Frequency Feature Extraction for Image Copy Move Forgery Detection

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Nayerdinzadeh Shirin; YOUSEFI MOHAMMAD REZA

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Majlesi Journal of Electrical Engineering Year:2021 | Volume:15 | Issue:3 Page(s): 69-80

Download Full-Text

View:

Download:

Cites:

Information Journal Paper

Title

An Enhanced Hybrid Method based on Local and Frequency Feature Extraction for Image Copy Move Forgery Detection

Author(s)

Nayerdinzadeh Shirin | YOUSEFI MOHAMMAD REZA | Issue Writer Certificate

Keywords

Copy Move Forgery Detection

Scale Invariant Feature Transform

Discrete Wavelet Transform

Local Binary Pattern

Symmetrical Images

Abstract

Today, due to the advent of the powerful photo editing software packages, it has become relatively easy to create forgery images. Recognizing the correctness of digital images becomes important when those images are used as evidence in legal, forensic, industrial, and military applications. One of the most common ways to forge images is copy move forgery, in which one part of the image is copied and pasted in another part of the same image. So far, various methods have been proposed for detecting copy move forgery, but these methods are not able to detect copy move forgery with different challenges of noise, rotation, scale, and detection of Symmetrical Images with high accuracy. In this paper, an enhanced hybrid method based on local and frequency feature extraction is presented for image Copy Move Forgery Detection, which has a very high resistance to above challenges, both individually and simultaneously and has provided good identification accuracy. In this method, the combination of Discrete Wavelet Transform, Scale Invariant Feature Transform and Local Binary Pattern are used simultaneously. The forged area is chosen in such a way that at least both methods used in this proposed method have consensus about the forgery of that area. Various experiments and analyses on the MICC database show that the proposed methods, despite the above challenges, have reached the accuracy of 98. 81% both separately and simultaneously, which shows significant improvement compared to other methods used in this field.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

APA: Copy

Nayerdinzadeh, Shirin, & YOUSEFI, MOHAMMAD REZA. (2021). An Enhanced Hybrid Method based on Local and Frequency Feature Extraction for Image Copy Move Forgery Detection. MAJLESI JOURNAL OF ELECTRICAL ENGINEERING, 15(3), 69-80. SID. https://sid.ir/paper/683213/en

Vancouver: Copy

Nayerdinzadeh Shirin, YOUSEFI MOHAMMAD REZA. An Enhanced Hybrid Method based on Local and Frequency Feature Extraction for Image Copy Move Forgery Detection. MAJLESI JOURNAL OF ELECTRICAL ENGINEERING[Internet]. 2021;15(3):69-80. Available from: https://sid.ir/paper/683213/en

IEEE: Copy

Shirin Nayerdinzadeh, and MOHAMMAD REZA YOUSEFI, “An Enhanced Hybrid Method based on Local and Frequency Feature Extraction for Image Copy Move Forgery Detection,” MAJLESI JOURNAL OF ELECTRICAL ENGINEERING, vol. 15, no. 3, pp. 69–80, 2021, [Online]. Available: https://sid.ir/paper/683213/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops