Work place: MPSTME, NMIMS University, Mumbai, India
Research Interests: Information-Theoretic Security, Network Security, Computer Networks, Computer systems and computational processes
Dr Uttam D. Kolekar received Ph.D. degree from the Bharathi Vidyapeeth University, Pune in Electronics Engineering in 2008. He has been working as Principal at A. P. Shah Institute of Technology, Thane. He has total 23 years teaching experience at various posts such as Lecturer, Assistant professor, Professor, Head of Department, Dean and Director at various Institutes of Mumbai University. He is a research guide at various universities in India and more than 5 candidates are working under him as research scholars from different institutes and Industries like TCS. He has more than 15 papers in national and international Journals and conferences against his name. He is also a reviewer for international journals like IEEE transactions. He is a fellow member of (IETE), Life member of ISTE & ISNT also he is a senior member of the international association of Computer science & information technology. He conducts seminars on mobile Ad-hock network, Mobile computing, GSM, GPRS, and UMTS. He is actively involved as a reviewer for many international conferences. He has addressed many workshops on wireless networks, Sensor networks, and Cyber security.
DOI: https://doi.org/10.5815/ijigsp.2016.04.04, Pub. Date: 8 Apr. 2016
Images are an integral part of advertisements. Images make the web pages heavy. It increases the response time if the size of the image is large and or available bandwidth is low. The consequence of it is viewer may lose his interest in the particular advertisement if he has to wait for a longer time. Image compression is one of the solutions to this problem. In advertisement images, ROI is of prime importance. Though the context of ROI and background regions are not of prime importance, they cannot be totally discarded. This paper investigates the effect of ROI coding on JPEG2000 performance. It proposes Multiple ROI (MROI) coding for compression of natural and advertisement images at moderate compression ratio. The proposed MROI coding prioritizes ROI codeblocks according to the ROI importance, and contribution of ROI in the specific ROI codeblock. It improves fine-grain accuracy at codeblock level also efficiently utilize the given bit budget with a negligible increase in encoding time.[...] Read more.
DOI: https://doi.org/10.5815/ijigsp.2015.08.07, Pub. Date: 8 Jul. 2015
The scale of salient object in an image is not a known priori, therefore to detect salient objects accurately multiple scale analysis is used by saliency detection models. However, multiple scale analysis makes the saliency detection slow. Fast and accurate saliency detection is essential to obtain Region of Interest in image processing applications. This paper proposes a scale space reduction with interpolation to speed up the saliency detection. To demonstrate the concept, this method is integrated with Hypercomplex Fourier Transform saliency detection which reduced the computational complexity from O(N) to O(N/2).[...] Read more.
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