Affiliation:
1. ERZİNCAN BİNALİ YILDIRIM ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ, BİLGİSAYAR MÜHENDİSLİĞİ BÖLÜMÜ
Abstract
Because digital images may contain a variety of data, they are regarded as an important source for information sharing. Also, images are widely used as evidence in a variety of real-life cases. The rapid rise in popularity of digital photographs is due to the improvement of technologies. Several software programs have been developed in recent years to modify digital images, such as Photoshop and Corel Photo, however these programs are now being used extensively for forgery. Because of technological advancements, it is difficult for people to recognize faked images with their naked eyes Therefore, in this study, the features used in forgery detection problems are combined to ensure accurate labeling of even forgery images that are difficult to detect. Stronger feature is obtained by combining Speeded-Up Robust Features (SURF) and Maximally Stable Extremal Regions (MSER). Considering the experimental results; it has been observed that the use of the proposed method, which is obtained as a result of combining the two methods in copy-move forgery detection problems, is more successful than using the SURF and MSER features separately.
Publisher
Omer Halisdemir Universitesi
Subject
General Economics, Econometrics and Finance
Reference36 articles.
1. [1] M. A. Qureshi and M. Deriche, “A bibliography of pixel-based blind image forgery detection techniques,” Signal Processing: Image Communication, vol. 39, pp. 46–74, 2015, doi: 10.1016/j.image.2015.08.008.
2. [2] M. Kashif, T. M. Deserno, D. Haak, and S. Jonas, “Feature description with SIFT, SURF, BRIEF, BRISK, or FREAK? A general question answered for bone age assessment,” Computers in Biology and Medicine, vol. 68, no. November, pp. 67–75, 2016, doi: 10.1016/j.compbiomed.2015.11.006.
3. [3] K. Asghar, Z. Habib, and M. Hussain, “Copy-move and splicing image forgery detection and localization techniques: a review,” Australian Journal of Forensic Sciences, vol. 49, no. 3, pp. 281–307, 2017, doi: 10.1080/00450618.2016.1153711.
4. [4] T. Mahmood, T. Nawaz, A. Irtaza, R. Ashraf, M. Shah, and M. T. Mahmood, “Copy-Move Forgery Detection Technique for Forensic Analysis in Digital Images,” Mathematical Problems in Engineering, vol. 2016, 2016, doi: 10.1155/2016/8713202.
5. [5] O. I. Al-Sanjary and G. Sulong, “Detection of video forgery: A review of literature,” Journal of Theoretical and Applied Information Technology, vol. 74, no. 2, pp. 207–220, 2015.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献