Goutam Sanyal

Work place: National Institute of Technology, Durgapur, WB, INDIA

E-mail: nitgsanyal@gmail.com


Research Interests: Computer Vision, Natural Language Processing, Solid Modeling, Network Architecture, Network Security, Computing Platform, Analysis of Algorithms


Gautam Sanyal is a member of the IEEE. He has received his B.E and M. Tech degree from National Institute of Technology (NIT), Durgapur, India. He has received Ph.D. (Engg.) from Jadavpur University, Kolkata, India, in the area of Robot Vision.

He possesses an experience of more than 25 years in the field of teaching and research. He has published nearly 68 papers in International and National Journals / Conferences. Three Ph. Ds (Engg.) have already been awarded under his guidance. At present he is guiding six Ph. Ds scholars in the field of steganography, Cellular Network, High Performance Computing and Computer Vision. He has guided over 10 PG and 100 UG thesis. His research interests include Natural Language Processing, Stochastic modeling of network traffic, High Performance Computing, Computer Vision. He is presently working as a Professor in the department of Computer Science and Engineering and also holding the post of Dean (Students’ Welfare) at National Institute of Technology, Durgapur, India.

Author Articles
A Novel Approach of Text Steganography using Nonlinear Character Positions (NCP)

By Sabyasachi Samanta Saurabh Dutta Goutam Sanyal

DOI: https://doi.org/10.5815/ijcnis.2014.01.08, Pub. Date: 8 Nov. 2013

Usually, the steganographic algorithms employ images, audio, video or text files as the medium to ensure hidden exchange of information between multiple contenders and to protect the data from the prying eyes. This paper presents a survey of text steganography method used for    hiding secret information inside some cover text. Here the text steganography algorithms based on modification of font format, font style et cetera, has advantages of great capacity, good imperceptibility and wide application range. The nonlinear character positions of different pages are targeted through out the cover with insignificant modification.  As compared to other methods, we believe that the approaches proposed convey superior randomness and thus support higher security.

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Classification of SAR Images Based on Entropy

By Debabrata Samanta Goutam Sanyal

DOI: https://doi.org/10.5815/ijitcs.2012.12.09, Pub. Date: 8 Nov. 2012

SAR image classification is the progression of separating or grouping an image into different parts. The good feat of recognition algorithms based on the quality of classified image. The good recital of recognition algorithms depend on the quality of classified image. The proposed classification method is hierarchical: classes which are difficult to distinguish are grouped.An important problem in SAR image application is accurate classification. In this paper, we developed a new methodology of SAR image Classification by Entropy. The severance between different groups or classes is based on logistic and multi-nominal regression, which finds the best combination of features to make the separation and at the same time perform a feature selection depending on Grouped –Entropy value.

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Other Articles