relative sub-image based features for leaf recognition using support vector machine
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.
leaf recognition support vector machine plant classification relative sub-images coefficients feature extraction