Samrendra Nath Panda

Work place: Department of Chemistry, Vikash Group of Institution



Research Interests: Engineering, Environmental Sciences, Earth & Environmental Sciences


Dr Samarendra Nath Panda received his PhD degree from 55 years old and renowned Government University as Sambalpur University situated at Western part of state Odisha, India. He has received his M.Phil. MSc. Degree from Sambalpur University. Currently he is serving as Director and Professor of Educational Institution at Vikash Group of Institution, Bargarh. Previously he has served as Principal of many Private Degree and Junior colleges. He has 20 years of teaching and 10 years of research experience. He has published many referred journals and presented International and National Conferences. His current research focuses in Photochemistry, Molecular Chemistry, and Organic chemistry; recently he has developed his research interest in Socio Economic Environmental Engineering.

Author Articles
Automatic Dead Zone Detection in 2-D Leaf Image Using Clustering and Segmentation Technique

By Rajat Kumar Sahoo Ritu Panda Ram Chandra Barik Samrendra Nath Panda

DOI:, Pub. Date: 8 Oct. 2018

Plant is a gift of almighty to the living being in the earth. Leaf is an essential component for any types of plant including crops, fruit and vegetables. Before the scheduled decay of the leaf due to deficiency there are patches of dead zone spot or sections generally visible. This paper introduces a novel image based analysis to identify patches of dead zone spot or sections generally visible due to deficiency. Clustering, colour object based segmentation and colour transformation techniques using significant salient features identification are applied over 12 plant leaves collected naturally from gardens and crop fields. Hue, saturation and Value based and L*a*b* colour model based object analysis is being applied over diseased leaf and portion of leaf to identify the dead zone automatically. Derivative based edge analysis is being applied to identify the outline edge and dead zone segmentation in leaf image. K-means clustering has played an important role to cluster dead zone using colour based object area segmentation.

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