Article
Image Segmentation Using Efcm for Banana Stem Disease Identification
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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.
R. Aravind and D. Maheswari, “Image segmentation using efcm for banana stem disease identification,” Turkish Journal of Computer and Mathematics Education, vol. 11, no. 3, pp. 1977–1996, 2020.
Aravind R, Maheswari D. Image segmentation using efcm for banana stem disease identification. Turkish Journal of Computer and Mathematics Education. 2020;11(3):1977–1996.
Aravind, R. and Maheswari, D. (2020), ‘Image segmentation using efcm for banana stem disease identification’, Turkish Journal of Computer and Mathematics Education, 11(3), pp. 1977–1996.
Aravind, R., and D. Maheswari. “Image Segmentation Using Efcm for Banana Stem Disease Identification.” Turkish Journal of Computer and Mathematics Education, vol. 11, no. 3, 2020, pp. 1977–1996.
Aravind, R., and D. Maheswari. “Image Segmentation Using Efcm for Banana Stem Disease Identification.” Turkish Journal of Computer and Mathematics Education 11, no. 3 (2020): 1977–1996.
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Published by: Engineering Journals


