Turkish Journal of Computer and Mathematics Education
Journal license

Journal

Turkish Journal of Computer and Mathematics Education


Volume
& Issue

Volume 11, Issue 3


Published
on


Pages

1977-1996


DOI

Article

Image Segmentation Using Efcm for Banana Stem Disease Identification


Authors

R. Aravind Affiliation:
RVS College of Arts and Science, Coimbatore, India
and D. Maheswari Affiliation:
RVS College of Arts and Science, Coimbatore, India


Abstract

Image Segmentation is the interaction by which an advanced image is divided into different subgroups (of pixels) called Image Objects, which can diminish the intricacy of the image, and accordingly examining the image gets less difficult. This paper portrays another automatic image segmentation methodology for segmenting plants. This paper presents straightforward methodology towards plant growth analysis Enhanced Fuzzy C - Means clustering algorithm is utilized to segment the region of interest, morphological shape analysis is applied to the Image Segmentation for Banana Plant. The strategy is highly promising nearby accuracy agriculture when we have large area to monitor.


Keywords

Image Segmentation, Enhanced Fuzzy C - Means clustering algorithm, Plant Monitoring System


Citation

Aravind, R. & Maheswari, D. (2020). Image segmentation using efcm for banana stem disease identification. Turkish Journal of Computer and Mathematics Education, 11(3), 1977–1996.

Published by: Engineering Journals

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