MedLeaf: Mobile biodiversity informatics tool for mapping and identifying Indonesian medicinal Plants

We presents a mobile biodiversity informatics tools for identifying and mapping Indonesian medicinal plants. The system — called MedLeaf — has been developed as a prototype data resource for documenting, integrating, disseminating, and identifying of Indonesian medicinal plants. Identification of medicinal plant is done automatically based on digital image processing. Fuzzy Local Binary Pattern (LBP) and geometrical features are used to extract leaves features. Probabilistic Neural Network is used as classifier for discrimination. Data set consist of 85 species of Indonesian medicinal plants with 3,502 leaves digital images. Our results indicate that combination of leaves features outperform than using single features with accuracy 88.5%. The distribution of medicinal plants can be shown on mobile phone using GIS application. The application is essential to help people identify the medicinal plants and disseminate information of medicinal plants distribution in Indonesia.