J. V. Desai

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



Research Interests: Computing Platform, Image Processing, Image Manipulation, Image Compression, Computer Architecture and Organization, Autonomic Computing


Prof. J V. Desai has completed his PhD form IIT Bombay. He has over 32 years‟ experience in teaching and research. He is currently Professor and Dean at Mody University of Science and Technology, Lakshmangarh. He has guided 7 PhDs and many M. Tech. scholars. He has published numerous research articles in many international conferences and journals. He has research grants worth many lacs from government and private organizations. He is senior member of many professional bodies like IEEE. He is reviewer of many reputed international journals and conferences. His research interest are Soft Computing, Modeling & Simulation, and Image & Signal Processing.

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

By Sunil Kumar J. V. Desai Shaktidev Mukherjee

DOI: https://doi.org/10.5815/ijigsp.2015.06.05, 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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