Species classification of aquatic plants using PSVM and ANFIS

Authors:
S. Abirami;V. Ramalingam;S. Palanivel
Affiliations:
Dept. of Computer Science and Engg, Annamalai University, Chidambaram, India;Dept. of Computer Science and Engg, Annamalai University, Chidambaram, India;Dept. of Computer Science and Engg, Annamalai University, Chidambaram, India
Venue:
Pattern Recognition and Image Analysis
Year:
2013

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Abstract

This work presents a method for plant species identification using the images of flowers. It focuses on the stable feature extraction of flowers such as color, texture and shape features in addition to fractal dimension. Color based segmentation using K-means clustering and active contour model is used to extract the color features. Texture segmentation using texture filter is used to segment the image and obtain texture features. Sobel, Prewitt and Robert operators are used to extract the boundary of image and to obtain the shape features. Classification of the plants is done using Proximal Support Vector Machine (PSVM) and Adaptive Neuro Fuzzy Inference System (ANFIS) classifiers.