Plant Disease Leaf Image Segmentation Using K-Means Clustering Based on Internet of Things

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Year:
2016
Type of Publication:
Article
Keywords:
Agricultural Internet of Things, Plant Disease Monitoring, Plant Disease Leaf Image Segmentation, K means Clustering, Internet of Things IOT
Authors:
Wang, Yun Shi Xuqi; Zhang, Shanwen
Journal:
IJRAS
Volume:
3
Number:
2
Pages:
51-54
Month:
March
ISSN:
2348-3997
Note:
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. CC BY-NC-SA 4.0 Creative Commons License: https://creativecommons.org/licenses/by-nc-sa/4.0/
Abstract:
The internet of things has been employed to recognize and monitor the plant diseases, in which the key process is the plant disease leaf image segmentation. Based on K-means clustering, a plant disease leaf image segmentation method is proposed in this paper. The plant disease leaf images are collected by the Internet of Things (IOT). Select an initial partition with k clusters, and a new partition is generated by assigning each, pattern to its closest cluster. Then compute new clusters. After several iterations, the spot image is obtained. The experimental results show that the proposed method is a robust for plant disease leaf image segmentation.
Full text: IJRAS_355_Final.pdf

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