RGB Görüntüler İçin Düşük Maliyetli Bir Görüntü Tahrif Tespiti Yöntemi Uygulaması

Yıl 2022, Cilt: 12 Sayı: 2, 105 - 118, 31.12.2022

Hüseyin Bilal Macit

https://doi.org/10.55024/buyasambid.1093220

Öz

Gelişen teknoloji sayesinde internet üzerinde çok sayıda görüntü transfer edilebilmektedir. Bu görüntülerin büyük çoğunluğu sosyal medya platformlarına yükleniyor ve düşük düzeyde mahremiyete sahip. Dijital görüntülere erişimin kolay olması ve görüntünün kolayca tahrif edilebilmesi nedeniyle, manipüle edilmiş görüntüler çeşitli sahtecilik ve dolandırıcılık yöntemlerinde kullanılabilmektedir. Sayısal görüntünün orijinal mi yoksa tahrifli edilmiş mi olduğunu belirlemek için literatürde çeşitli algoritmalar önerilmiştir. Bu çalışmada, basit ve düşük işlem karmaşıklığına sahip bir hata tespit mekanizması olan çift eşlik biti yöntemi, 3 katmanlı renkli görüntülerin katman verilerine steganografik bir yaklaşımla uygulanmakta ve sayısal görüntülerde manipülasyonun tespit edilmesi amaçlanmaktadır.

Anahtar Kelimeler

LSB, Görüntü Tahrifi, Eşlik Kodu

Implementation of a Low-Cost Tamper Detection Method for RGB Images

Öz

Thanks to the developing technology, a large number of images are transferred on the internet. The vast majority of these images are uploaded to social media platforms and have a low level of privacy. Due to the ease of access to digital images and the fact that the image can be easily tampered with, manipulated images can be used in various forgery and fraud methods. Various algorithms have been proposed in the literature to determine whether the digital image is original or tampered. In this study, the even parity bit method, which is a very simple and low-complex error detection mechanism, is applied to the layer data of 3-layer color images with a steganographic approach and it is aimed to detect tampering in digital images.

Anahtar Kelimeler

LSB, Image Tampering, Parity Code, Görüntü Tahrifi, Görüntü Tahrifi, Görüntü Tahrifi, Eşlik Kodu, Eşlik Kodu

Kaynakça

• Alamro L. and Nooraini Y. (2017) Copy-move forgery detection using integrated DWT and SURF, Journal of Telecommunication, Electronic and Computer Engineering (JTEC), Vol. 9, pp. 67-71.
• Deshpande P. and Kanikar P. (2012) Pixel Based Image Forgery Detection Techniques, International Journal of Engineering Research and Applications, Vol. (2)3, pp.539-543.
• Gulivindala S. and Rao C.S. (2013) Tampering Detection Algorithms: A Comparative Study, International Journal of Engineering Research and Development, e-ISSN: 2278-067X, p-ISSN: 2278-800X, Vol. (7)5, pp. 82-86.
• Macit H.B. and Koyun A. (2019) Tamper Detection and Recovery on RGB Images, International Conference on Artificial Intelligence and Applied Mathematics in Engineering, pp. 972-981, DOI: 10.1007/978-3-030-36178-5_86.
• Mishra M. and Adhikary M.C. (2013) Digital Image Tamper Detection Techniques - A Comprehensive Study, International Journal of Computer Science and Business Informatics, ISSN: 1694-2108, Vol. (2)1.
• Qureshi M.A. and Deriche M. (2015) A bibliography of pixel-based blind image forgery detection techniques, Signal Processing: Image Communication, Vol. 39, pp. 46-74, DOI:10.1016/j.image.2015.08.008.
• Senekane M., Mafu M., Maseli M. and Taleme B.M. (2021) A quantum algorithm for single parity check code, IEEE 2021 Africon, DOI: 10.1109/AFRICON51333.2021.9570857.
• Shashidhar T.M. and Ramesh K.B. (2017) Reviewing the Effectivity Factor in Existing Techniques of Image Forensics, International Journal of Electrical and Computer Engineering, Vol. (7)6, pp.3558-3569, ISSN: 2088-8708, DOI: 10.11591/ijece.v7i6.pp3558-3569.
• Stoilov P.S., Hristov G. and Zahariev P. (2021) Analysis Of The Least Significant Bit Subtitution Algorithm For Image Stenography, Proceedings Of University Of Ruse, Vol. 60, Book. 3.2, pp. 207-213.
• Şahin A., Buluş E. and Sakallı M.T. (2006) 24-Bit Renkli Resimler Üzerinde En Önemsiz Bite Ekleme Yöntemini Kullanarak Bilgi Gizleme, Trakya Univ J Sci, Vol. 7(1), pp. 17-22, ISSN 1305-6468.
• Taha B.T., Ngadiran R., Ehkan P. and Sultan M.T. (2018) Image Tamper Detection and Recovery Using Lifting Scheme Based Fragile Watermarking”, Journal of Theoretical and Applied Information Technology, Vol. (96)8, ISSN: 1992-8645.
• Wang M.S. and Chen W.C. (2007) A majority-voting based watermarking scheme for color image tamper detection and recovery, Computer Standards & Interfaces, Vol. 29, pp. 561–570.
• Vaishnavi D. and Subashini T.S. (2015) Image Tamper Detection based on Edge Image and Chaotic Arnold Map, Indian Journal of Science and Technology, Vol. (8)6, pp. 548–555.
• Yeap Y.Y., Sheikh U.U. and Rahman A. (2018) Image forensic for digital image copy move forgery detection, IEEE 14th International Colloquium on Signal Processing & Its Applications (CSPA), DOI:10.1109/CSPA.2018.8368719.
• Zulfira F., Nuha H.H., Sudiharto D.W. and Utomo R.G. (2021) Modified Bit Parity Technique for Error Detection of 8 Bit Data, Proceedings of 9’th International Conference on Information and Communication Technology, pp. 517-521.