Work place: School of Technology & Applied Science, Edapally, Kochi-24, Kerala, India
E-mail: jeevanjeevan77@gmail.com
Website:
Research Interests: Image Processing, Image Manipulation, Image Compression
Biography
Jeevan K. M was born in Kerala, India on 28th may 1977. He obtained his Bachelor of Technology in Electronics and Communication Engineering from Rajiv Gandhi Institute of Technology, Kottayam, Kerala, India in 1999 and Master of Technology in Electronics and Communication from College of Engineering, Trivandrum, Kerala, India in 2002. He worked as a research fellow in Centre for Development of Advanced Computing (C-DAC), Trivandrum, Kerala, India and as a Hardware Design Engineer in many Multinational Companies. Currently he is working as an Associate Professor in the department of Electronics and Communication in Sreearayana Gurukulam College of Engineering, Ernakulam, Kerala. He has published papers in international journals and presented papers in national and international conferences. His areas of interest include signal processing and image processing.
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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