Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/1258
Title: FUZZY INFERENCE SYSTEM ALGORITHM OF PLANT CLASSIFICATION FOR TEA LEAF RECOGNITION
Authors: Arunpriya C
Antony Selvadoss Thanamani
Keywords: Classification algorithm
Fuzzy Inference System (FIS)
Leaf Recognition
Pre-processing
Issue Date: 2015
Publisher: Indian Journal of Science and Technology
Abstract: Background/Objectives: Biologists found that the morphological, physiological, bio-chemical and molecular methods of plant identification are found to be laborious and require great amount of technical knowledge. This research paper concentrates on the identification of varieties of tea using leaf images. It aims to identify the species in an easy and an accurate manner. Methods/Statistical analysis: The phases involved in this work are image pre processing, feature extraction and classification. Three classification algorithms such as Fuzzy Inference system, Radial basis function network and K-nearest neighbour were used and optimized to achieve a better accuracy and execution time. Results/Findings: The classification algorithm K-nearest neighbor, Radial basis function neural network and Fuzzy Inference System are trained with 40 samples and tested using 20 samples. Conclusions: Fuzz
URI: http://localhost:8080/xmlui/handle/123456789/1258
ISSN: Print:0974-6846
Online:0974-5645
Appears in Collections:International Journals

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