Cover page and Table of Contents: PDF (size: 784KB)
Full Text (PDF, 784KB), PP.22-30
Views: 0 Downloads: 0
Copy-move image forgery, block-based method, keypoint-based method, DCT, SURF
As the world has greatly experienced a serious advancement in the area of technological advancement over the years, the availability of lots of sophisticated and powerful image editing tools has been on the rise. These image editing tools have become easily available on the internet, which has made people who are a novice in the field of image editing, to be capable of tampering with an image easily without leaving any visible clue or trace behind, which has led to increase in digital images losing authenticity. This has led to developing various techniques for tackling authenticity and integrity of forged images. In this paper, a robust and enhanced algorithm is been developed in detecting copy-move forgery, which is done by hybridizing block-based DCT (Discrete Cosine Transform) technique and a keypoint-based SURF (Speeded-Up Robust Feature)technique using the MATLAB platform. The performance of the above technique has been compared with DCT and SURF techniques as well as other hybridized techniques in terms of precision, recall, FPR and accuracy metrics using MICC-F220 dataset. This technique works by applying DCT to the forged image, with the main goal of enhancing the detection rate of such image and then SURF is applied to the resulting image with the main goal of detecting those areas that are been tampered with on the image. It has been observed that this paper’s technique named HDS has an effective detection rate on the MICC-F220 dataset with multiple cloning attacks and other various attacks such as rotation, scaling, a combination of scaling plus rotation, blur, compression, and noise.
Joseph A. Ojeniyi, Bolaji O. Adedayo, Idris Ismaila, Abdulhamid M. Shafi’i," Hybridized Technique for Copy-Move Forgery Detection Using Discrete Cosine Transform and Speeded-Up Robust Feature Techniques", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.10, No.4, pp. 22-30, 2018. DOI: 10.5815/ijigsp.2018.04.03
M. Acedo. (2016, on 29th January, 2017). 5 Smart Ways To Use Digital Images In The Classroom. Available: http://www.teachthought.com/the-future-of-learning/technology/5-smart-ways-use-digital-images-classroom/
M. Sridevi, C. Mala, and S. Sanyam, "Comparative Study of Image Forgery and Copy-Move Techniques," in Advances in Computer Science, Engineering & Applications: Proceedings of the Second International Conference on Computer Science, Engineering and Applications (ICCSEA 2012), New Delhi, India. vol. 1, D. C. Wyld, J. Zizka, and D. Nagamalai, Eds., ed New York: Springer Science & Business Media, 2012, pp. 715-723.
S. Sahu,S. Kumar Nanda, and T. Mohapatra, " Digital Image Texture Classification and Detection Using Radon Transform," International Journal of Image, Graphics and Signal Processing(IJIGSP), vol. 5, pp. 38-48, 2013
E. Burns. (2016, on 27th January, 2017). Photo Editing Apps You Can Get for Free. Available: http://www.digitaltrends.com/computing/best-free-photo-editing-software/
S. K. Mankar and A. A. Gurjar, "Image Forgery Types and Their Detection: A Review," International Journal of Advanced Research in Computer Science and Software Engineering vol. 5, pp. 174-178, 2015.
Full Sail. (2017, on 29th January, 2017). Enhance Perfection With a Photo Retouching Career Available: http://www.theartcareerproject.com/photo-retouching/657/
T. H. Park, J. G. Han, Y. H. Moon, and I. K. Eom, "Image Splicing Detection Based on Inter-Scale 2D Joint Characteristic Function Moments in Wavelet Domain," EURASIP Journal on Image and Video Processing, vol. 2016, pp. 30-39, 2016.
J. Brown. (2016, on 29th January, 2017). Pentagon Is Developing Tech That Detects Fake Photos. Available: http://www.vocativ.com/356956/pentagon-doctored-photos/
B. George. (2016, on 29th January, 2017). 12 Historic Photographs that were actually Doctored (14 HQ Photos). Available: http://thechive.com/2012/02/07/12-historic-photographs-that-were-actually-doctored-14-hq-photos/
A. Dixit, and R. K. Gupta, " Copy-Move Image Forgery Detection a Review," International Journal of Image, Graphics and Signal Processing(IJIGSP), vol. 8, pp. 29-40, 2016.
H. Kaur and K. Kaur, "A Brief Survey of Different Techniques for Detecting Copy-Move Forgery," International Journal of Advanced Research in Computer Science and Software Engineering, vol. 5, pp. 875-882, 2015.
M. Al-Hammadi, "Copy Move Forgery Detection In Digital Images Based On Multiresolution Techniques," MSc, Computer Engineering, Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh., 2013.
G. K. Saini, and M. Mahajan,, " Improvement in Copy -Move Forgery Detection Using Hybrid Approach," International Journal of Modern Education and Computer Science(IJMECS), vol. 8, pp. 56-63, 2016.
S. Kumar, J. V. Desai, and S. Mukherjee, " Copy Move Forgery Detection in Contrast Variant Environment using Binary DCT Vectors," International Journal of Image, Graphics and Signal Processing(IJIGSP), vol. 7, pp. 38-44, 2015.
S. Bayram, H. T. Sencar, and N. Memon, "A survey of copy-move forgery detection techniques," in IEEE Western New York Image Processing Workshop, New York City, 2008, pp. 538-542.
N. B. A. Warif, A. W. A. Wahab, M. Y. I. Idris, R. Ramli, R. Salleh, S. Shamshirband, et al., "Copy-Move Forgery Detection: Survey, Challenges and Future Directions," Journal of Network and Computer Application, vol. 75, pp. 259-278, 2016.
A. Gupta, N. Tiwari, M. Chawla, and M. Shandilya, "An Image Encryption using Block based Transformation and Bit Rotation Technique," International Journal of Computer Applications, vol. 98, 2014.
J. Zheng, Y. Liu, J. Ren, T. Zhu, Y. Yan, and H. Yang, "Fusion of block and keypoints based approaches for effective copy-move image forgery detection," Multidimensional Systems and Signal Processing, vol. 27, pp. 989-1005, 2016.
R. Krishnamoorthy and G. Devasena, "A Block-Based Feature Extraction Approach for Texture Classification with Orthogonal Polynomials," in 5th National Conference on Computational Methods, Communication Techniques & Informatics (NCCCI 2017) New Delhi, India, 2017, pp. 16-20.
V. Anand, M. F. Hashmi, and A. G. Keskar, "A Copy Move Forgery Detection to Overcome Sustained Attacks Using Dyadic Wavelet Transform and SIFT Methods," in Intelligent Information and Database Systems: 6th Asian Conference, Aciids 2014, Bangkok, Thailand. vol. 8397, N. T. Nguyen, B. Attachoo, B. Trawiński, and K. Somboonviwat, Eds., ed Switzerland Springer International Publishing, 2014, pp. 530-542.
A. J. Fridrich, B. D. Soukal, and A. J. Lukáš, "Detection of copy-move forgery in digital images," in Digital Forensic Research Workshop, Cleveland, Ohio, USA, 2003.
Y. Huang, W. Lu, W. Sun, and D. Long, "Improved DCT-based detection of copy-move forgery in images," Forensic science international, vol. 206, pp. 178-184, 2011.
Y. Cao, T. Gao, L. Fan, and Q. Yang, "A robust detection algorithm for copy-move forgery in digital images," Forensic science international, vol. 214, pp. 33-43, 2012.
J. Zhao and J. Guo, "Passive forensics for copy-move image forgery using a method based on DCT and SVD," Forensic science international, vol. 233, pp. 158-166, 2013.
S. Kumar, J. Desai, and S. Mukherjee, "A fast DCT based method for copy move forgery detection," in 2013 IEEE Second International Conference on Image Information Processing (ICIIP), Shimla, India, 2013, pp. 649-654.
G. Fracastoro, S. M. Fosson, and E. Magli, "Steerable Discrete Cosine Transform," IEEE Transactions on Image Processing, vol. 26, pp. 303-314, 2017.
X. Bo, W. Junwen, L. Guangjie, and D. Yuewei, "Image copy-move forgery detection based on SURF," in International Conference on Multimedia information networking and security (MINES), Nanjing, China, 2010, pp. 889-892.
N. Hamid, A. Yahya, R. B. Ahmad, and O. M. Al-Qershi, "A Comparison between using SIFT and SURF for characteristic region based image steganography," International Journal of Computer Science Issues, vol. 9, pp. 110-116, 2012.
R. Raj and N. Joseph, "Keypoint Extraction Using SURF Algorithm for CMFD," Procedia Computer Science, vol. 93, pp. 375-381, 2016.
A. Katharotiya, S. Patel, and M. Goyani, "Comparative analysis between DCT & DWT techniques of image compression," Journal of Information Engineering and Applications, vol. 1, pp. 9-17, 2011.
R. C. Pandey, S. K. Singh, K. Shukla, and R. Agrawal, "Fast and robust passive copy-move forgery detection using SURF and SIFT image features," in 2014 9th International Conference on Industrial and Information Systems (ICIIS), Gwalior, India, 2014, pp. 1-6.
M. F. Hashmi, A. R. Hambarde, and A. G. Keskar, "Copy move forgery detection using DWT and SIFT features," in 2013 13th International Conference on Intelligent Systems Design and Applications (ISDA), Malaysia, 2013, pp. 188-193.
M. F. Hashmi, V. Anand, and A. G. Keskar, "Copy-move image forgery detection using an efficient and robust method combining un-decimated wavelet transform and scale invariant feature transform," Aasri Procedia, vol. 9, pp. 84-91, 2014.
H. Kaur, J. Saxena, and S. Singh, "Simulative Comparison of Copy-Move Forgery Detection Methods for Digital Images," International Journal of Electronics, Electrical and Computational System, vol. 4, pp. 62-66, 2015.
M. Singh and E. H. Singh, "Detection of Cloning Forgery Images using SURF + DWT and PCA," International Journal of Latest Engineering Research and Applications (IJLERA), vol. 1, pp. 1-10, 2016.
G. K. Saini, M. Mahajan, and P. Mohali, "Study of Copy Move Image Forgery Detection Based On Surf Algorithm," International Journal of Modern Electronics and Communication Engineering (IJMECE) vol. 4, pp. 46-49, 2016.