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Home > Archives > Volume 20, No 8 (2022) > Article

DOI: 10.14704/nq.2022.20.8.NQ44937

COCONUT TREE DISEASE SEGMENTATION USING FUZZY ROUGH C-MEANSCLUSTERING ALGORITHM

K.Loganathan, V.Mathavan, S.Vanakovarayan

Abstract

The occurrence of plant diseases has a negative impact on agricultural production. If plant diseases are not observed in time, it will lead huge lose for farmers. Early detection is the basis for effective prevention and control of plant diseases, and they play a vital role in the management and decision making of agricultural production. Coconut palms are affected by a number of diseases, some of which are dangerous and the disease gradually reduces the strength of thepalm causing severe loss in the yield. Coconut trees are also attacked by a number of fungi, bacteria, viruses and nematodes leading to significant quantitative and qualitative loss. In this paper, Fuzzy Rough C-Means (FRCM) segmentation algorithm is proposed to detect the Coconut tree diseases. The effectiveness of the proposed segmentationalgorithm is verified by comparing its results with that of the OTSU segmentation algorithm.

Keywords

Segmentation, image processing, Fuzzy, Rough C Means and Disease.

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