Sunil Kumar

Work place: Mody University of Science and Technology, Lakshmangarh, 332311, India



Research Interests: Algorithm Design, Image and Sound Processing, Processor Design, Computer systems and computational processes, Interaction Design


Sunil Kumar is working as Assistant Professor, Faculty of Engineering & Technology, Mody University of Science and Technology, Lakshmangarh. He has more than 12 years of UG and PG teaching experience after completing his M. Tech. in Computer Science & Engineering in 2002 from Kurukshetra University, Kurukshetra. He has supervised many B. Tech. and M. Tech projects. He has published many research papers in international conferences and journals. He is also reviewer of reputed journals. He is life member of Computer Society of India and current member of IEEE and ACM. His research interest are image forensics, algorithm design and soft computing.

Author Articles
Copy Move Forgery Detection in Contrast Variant Environment using Binary DCT Vectors

By Sunil Kumar J. V. Desai Shaktidev Mukherjee

DOI:, Pub. Date: 8 May 2015

Copy move forgery detection is a very popular research area and a lot of methods have been suggested by researchers. However, every method has its own merits and weaknesses and hence, new techniques are being continuously devised and analyzed. There are many post processing operations used by the manipulators to obstruct the forgery detection techniques. One such operation is changing the contrast of the whole image or copy moved regions, which many existing methods fail to address. A novel method using binary discrete cosine transform vectors is proposed to detect copy move forgery in the presence of contrast changes. The image is divided into overlapping blocks and DCT coefficients are calculated for these blocks. Feature vectors are created from these blocks using signs of the DCT coefficients. Coefficient of correlation is used to match resulting binary vectors. The experiments show that the proposed method is able to detect copy move forgery in presence of contrast changes. The proposed method is also invariant to other post processing operations like Gaussian noise, JPEG compression and little rotation and scaling. 

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