Vidya Prasad Shukla

Work place: Faculty of Engineering & Technology, Mody Institute of Technology & Science

E-mail: drsvprasad2k@yahoo.com

Website:

Research Interests: Computational Biology, Computer Vision, Image Manipulation, Solid Modeling, Image Processing, Medical Image Computing, Mathematics of Computing, Theory of Computation, Cellular Automata, Models of Computation

Biography

Vidya Prasad Shukla was born in India, in 1954. He received his M.Sc. (Applied Mathematics) in 1976, Ph.D. (Modelling and Computer Simulation) in 1982 and PG Dip. (Computational Hydraulic Engineering) in 1986 from Avadh University Faizabad, Indian Institute of Technology Kanpur and International Institute of Environmental & Hudraulic Engineering (Delft) the Netherlands respectively. He worked and officiated at various posts as Senior Research Officer, Chief Research Officer and HOD Computer Division at from Central Water and Power research Station (CWPRS), Pune from 1982 to 2003. Thereafter, he worked as a Professor in BIT, Sathyamangalam and NIT Durgapur. He has joined as a Professor in Mody Institute of Technology & Science, Deemed University Laxmangarh in 2009. He has published over 57 papers in refereed journals and conference proceedings and written 29 technical reports on various clients sponsored research projects of international/national importance. He is an editor of the book ―Development of Coastal Engineering‖ from CWPRS, Pune. His current research interest includes Computer Simulation & Modeling, Image processing, Cellular Automata, Soft-Computing, Computer Vision, Nanotech-simulation, Operations Research, Mathematical Biology, Modeling of Arms Race of Nations.

Author Articles
Texture Features based Blur Classification in Barcode Images

By Shamik Tiwari Vidya Prasad Shukla Sangappa Biradar Ajay Singh

DOI: https://doi.org/10.5815/ijieeb.2013.05.05, Pub. Date: 8 Nov. 2013

Blur is an undesirable phenomenon which appears as image degradation. Blur classification is extremely desirable before application of any blur parameters estimation approach in case of blind restoration of barcode image. A novel approach to classify blur in motion, defocus, and co-existence of both blur categories is presented in this paper. The key idea involves statistical features extraction of blur pattern in frequency domain and designing of blur classification system with feed forward neural network.

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