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S. Krishnakumar

Work place: School of Technology & Applied Science, Edapally, Kochi-24, Kerala, India

E-mail: drkrishsan@gmail.com

Website:

Research Interests: Image Processing, Image Manipulation, Image Compression, Computational Science and Engineering

Biography

S. Krishnakumar was born in Kerala, India on 28th May, 1964. He completed his M.Sc. in Physics with Electronics specialization in 1987 and was awarded with Ph.D. in Thin Film Devices in 1995 from Mahatma Gandhi University, Kottayam, Kerala, India. He received M.Tech. in Computer Science from Allahabad Agricultural Institute – Deemed University (renamed as Sam Higginbottom Institute of Agriculture, Technology and Sciences) in 2006 and also completed MCA from IGNOU in 2010. He has 18 years teaching experience in Electronics and Computer Science subjects for graduate and post-graduate courses. Currently he is the Regional Director of University College of Applied Sciences, Edappally, Kochi under Mahatma Gandhi University, Kottayam. He has 11 publications in International Journal and Conferences. His areas of research include Thin Film Electronic Devices, VLSI Design and Image Processing. Dr. Krishnakumar is an Associate Member of Institution of Engineers, India. He was a member of Board of studies of University of Calicut and a member of Academic Council of Mahatma Gandhi University, Kottayam for 4 years.

Author Articles
An Algorithm for the Simulation of Pseudo Hexagonal Image Structure Using MATLAB

By Jeevan K. M. S. Krishnakumar

DOI: https://doi.org/10.5815/ijigsp.2016.06.07, Pub. Date: 8 Jun. 2016

Hexagonal structure is a different approach to represent an image rather than the traditional square structure. Hexagonal shaped pixels are used in hexagonal structure representation of images. The hexagonal structure closely resembles the structure of human visual systems (HVS) because the photo receptors found in human retina are arranged in a hexagonal manner. Also curved structure can be well represented using hexagonal structure. So if we could able to represent the image in hexagonal domain, the computer vision will be as close to human vision. But in the present scenario there is no hardware available to capture or display hexagonal images. So we have to simulate a hexagonal grid on a regular square pixel image for further processing in hexagonal domain. In this paper, a new method for constricting a pseudo hexagonal structure using square pixel is presented. This method preserves the important property of hexagonal architecture that each pixel has exactly six surrounding neighbors. This method also preserves the equidistance property of hexagonal pixels. 

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