Classification of Indian Herbal Leaf with Random Forest Classifier
Herbal Leaf is normally used for preparing medicines. This includes images taken from the locality of West Bengal mainly Kolkata, with white background. By taking into account this problem of image classification, this research tries to identify herbal leaves based on the images taken on white background. Therefore, this research includes an image processing algorithm and Otsu segmentation. Then, the leaf image features are identified, based on the characteristics of the shape and texture. Herbal leaf shape and color features produce high accuracy only when both are applied at the same time. In this research, morphological features were used for shape feature extraction. The contribution of this study is using the proposed image enhancement and segmentation algorithm so that the features of the image can be extracted based on shape and color descriptors. The classification accuracy in this study has reached 97.8% with Random Forest Classifier.
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