Identification of Philippine herbal medicine plant leaf using artificial neural network

College

Gokongwei College of Engineering

Department/Unit

Manufacturing Engineering and Management

Document Type

Conference Proceeding

Source Title

HNICEM 2017 - 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management

Volume

2018-January

First Page

1

Last Page

8

Publication Date

7-2-2017

Abstract

The study described in this paper consists of a system that involves image processing techniques to extract relevant features related to leaf in conjunction with using artificial neural network in order to detect and identify some Philippine herbal plants. Real samples of twelve different herbal medicine plant leaves are collected where each leaf are isolated in single image. Several features are extracted using techniques in image processing. With the artificial neural network acting as autonomous brain network, the system can identify the species of the herbal medicine plant leaves being tested. The system can also provide information about the diseases the herbal plant can cure. For the training, a features dataset of 600 images coming from 50 images per herbal plant are used. With the aid of Python, a neural network model with optimized parameters are established producing 98.16 % identification for the whole dataset. To evaluate the actual performance of the system, a separate 72 sample images of herbal plants are tested with the neural network model implemented in MATLAB. Experimental results demonstrate a 98.61 % accuracy of herbal plant identification. © 2017 IEEE.

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Digitial Object Identifier (DOI)

10.1109/HNICEM.2017.8269470

Disciplines

Manufacturing

Keywords

Medicinal plants--Philippines—Identification; Image processing—Digital techniques; Neural networks (Computer science)

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