Pomegranate Fruit Diseases Identification and Grading

DOI

10.2991/iccasp-16.2017.96How to use a DOI?

Keywords

Pomegranate, K-means, SVM (support vector machine), mean, variance

Abstract

India is one of the well-known country in world, in the area of pharmacy specially food horticulture. India pro-duces nearly 5.00 lacks tones/annum pomegranate. Fruit gradation is one of the most vital parts in fruit horti-culture. The project design presented by this paper is from same problematic area. In our project design we developed systems which classify diseases affecting pomegranates using K-means clustering and SVM techniques. We are classifying the different pomegranate variety in accordance with their diseases. This paper deals with pomegranate grading and identification of disease system with judging parameters. The specialty of design is it creates a model which helps to decide appropriate criteria for healthy fruit. This project design is acts as advance system model in Indian horticulture for deciding ranges of mean, variance, entropy values by which the quality of fruit is decided. These parameters are judging parameters of our project design.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - D. Gaikwad
AU  - K. Karande
AU  - H. Deshpande
PY  - 2016/12
DA  - 2016/12
TI  - Pomegranate Fruit Diseases Identification and Grading
BT  - Proceedings of the International Conference on Communication and Signal Processing 2016 (ICCASP 2016)
PB  - Atlantis Press
SP  - 672
EP  - 679
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasp-16.2017.96
DO  - 10.2991/iccasp-16.2017.96
ID  - Gaikwad2016/12
ER  -