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Shape is the main information for leaf feature that most of the current literatures in leaf identification utilize the whole leaf for feature extraction and to be used in the leaf identification process. In this paper, study of half-leaf features extraction for leaf identification is carried out and the results are compared with the results obtained from the leaf identification based on a full-leaf features extraction. Identification and classification is based on shape features that are represented as cosines and sinus angles. Ten classifiers obtained from WEKA and seven ensemble methods are used to compare their performance accuracies over this data. The classifiers were trained using 65 leaves in order to classify 5 different species of preliminary collection of Malaysian medicinal plants. The result shows that half-leaf features extraction can be used for leaf identification without decreasing the predictive accuracy.

Comparison of Half and Full-Leaf Shape Feature Extraction for Malaysian Medicinal Leaf Identification and Classification