ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
A method of plant classification based on wavelet transforms and support vector machines
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Recognition of leaf images based on shape features using a hypersphere classifier
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Leaf recognition based on the combination of wavelet transform and gaussian interpolation
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Detection of disease using block-based unsupervised natural plant leaf color image segmentation
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I
Plant leaf disease detection using gabor wavelet transform
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
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In this paper, we extract our proposed RSC features from leaf images and use SVM classifier to implement an automated leaf recognition system for plant leaf identification and classification. Automatic plant species identification and classification is helpful in biology, forest and agriculture to study and discover new species in plant in botanical gardens and is also used to recognize the medicinal plants to prepare herbal medicines. Here, 300 leaf features are extracted from a single leaf of 624 leaf dataset to classify 23 different kinds of plant species with an average accuracy of 95%. Compared with other approaches, our proposed algorithm has less time complexity and is easy to implementation with higher accuracy.