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Reseach Article

Species Classification of Aquatic Plants using GRNN and ANFIS

by S. Abirami, V. Ramalingam, S. Palanivel
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 47 - Number 4
Year of Publication: 2012
Authors: S. Abirami, V. Ramalingam, S. Palanivel

S. Abirami, V. Ramalingam, S. Palanivel . Species Classification of Aquatic Plants using GRNN and ANFIS. International Journal of Computer Applications. 47, 4 ( June 2012), 47-52. DOI=10.5120/7180-9863

@article{ 10.5120/7180-9863,
author = { S. Abirami, V. Ramalingam, S. Palanivel },
title = { Species Classification of Aquatic Plants using GRNN and ANFIS },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 47 },
number = { 4 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 47-52 },
numpages = {9},
url = { },
doi = { 10.5120/7180-9863 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T20:41:03.422794+05:30
%A S. Abirami
%A V. Ramalingam
%A S. Palanivel
%T Species Classification of Aquatic Plants using GRNN and ANFIS
%J International Journal of Computer Applications
%@ 0975-8887
%V 47
%N 4
%P 47-52
%D 2012
%I Foundation of Computer Science (FCS), NY, USA

This work presents a method for plant species identification using the images of flowers. It focuses on the stable features of flowers such as color, texture and shape. K-means clustering is used to extract the color features. Texture segmentation is done using texture filters. Edge detectors are used to trace the boundary of the image and hence the shape features. Color, texture and shape features are extracted from 400 images of flowers. Classification of plants into dry land plants and aquatic plants, the aquatic plant species into wet and marsh aquatic plants, wet aquatic plants into iridaceae and epilobium family and marsh aquatic plants into malvaceae and onagraceae family, the iridaceae family into babiana and crocus species, the family epilobium into canum and hirsutum, the family malvaceae into mallow and pavonia, the family onagraceae into fuschia and ludwigia species are done using Generalized Regression Neural Network (GRNN) and Adaptive Neural Fuzzy Inference System (ANFIS) classifiers.

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Index Terms

Computer Science
Information Sciences


K-means Clustering Texture Filters Cross Fold Validation Pattern Recognition Tools