DOI : https://doi.org/10.18517/ijaseit.3.2.287

MedLeaf: Mobile Application for Medicinal Plant Identification Based on Leaf Image

Desta Sandya Prasvita (1), Yeni Herdiyeni (2)
(1) Department of Computer Science, Faculty of Mathematic and Natural Science Bogor Agricultural University, West Java, Indonesia
(2) Department of Computer Science, Faculty of Mathematic and Natural Science Bogor Agricultural University, West Java, Indonesia
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How to cite (IJASEIT) :
Prasvita, Desta Sandya, and Yeni Herdiyeni. “MedLeaf: Mobile Application for Medicinal Plant Identification Based on Leaf Image”. International Journal on Advanced Science, Engineering and Information Technology, vol. 3, no. 2, Apr. 2013, pp. 103-6, doi:10.18517/ijaseit.3.2.287.
Citation Format :
This research proposes MedLeaf as a new mobile application for medicinal plants identification based on leaf image. The application runs on the Android operating system. MedLeaf has two main functionalities, i.e. medicinal plants identification and document searching of medicinal plant. We used Local Binary Pattern to extract leaf texture and Probabilistic Neural Network to classify the image. In this research, we used30 species of Indonesian medicinal plants and each species consists of 48 digital leaf images. To evaluate user satisfaction of the application we used questionnaire based on heuristic evaluation. The evaluation result shows that MedLeaf is promising for medicinal plants identification. MedLeaf will help botanical garden or natural reserve park management to identify medicinal plant, discover new plant species, plant taxonomy and so on. Also, it will help individual, groups and communities to find unused and undeveloped their skill to optimize the potential of medicinal plants. As the results, MedLeaf will increase of their resources, capitals, and economic wealth.

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