Image Retrieval Based on Color, Shape, and Texture for Ornamental Leaf with Medicinal Functionality Images

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Kohei Arai 1 Indra Nugraha Abdullah 1 Hiroshi Okumura 1

1. Graduate School of Science and Engineering, Saga University, Saga, Japan

* Corresponding author.


Received: 14 Feb. 2014 / Revised: 3 Apr. 2014 / Accepted: 7 May 2014 / Published: 8 Jun. 2014

Index Terms

Image retrieval, hsv histogram, zernike moments, dyadic wavelet, bayesian weighting, ornamental leaf, medicinal leaf


This research is focusing on ornamental leaf with dual functionalities, which are ornamental and medicinal functionalities. However, only few people know about the medicinal functionality of this plant. In Indonesia, this plant is also easy to find because mostly cultivates in front of the house. If its medicinal function and that easiness are taken into consideration, this leaf should be an option towards the full chemical-based medicines. This image retrieval system utilizes color, shape, and texture features from leaf images. HSV-based color histogram, Zernike complex moments, and Dyadic wavelet transformation are the color, shape, and texture features extractor methods, respectively. We also implement the Bayesian automatic weighting formula instead of assignment of static weighting factor. From the results, this proposed method is very powerful from any rotation, lighting, and perspective changes.

Cite This Paper

Kohei Arai, Indra Nugraha Abdullah, Hiroshi Okumura,"Image Retrieval Based on Color, Shape, and Texture for Ornamental Leaf with Medicinal Functionality Images", IJIGSP, vol.6, no.7, pp.10-18, 2014. DOI: 10.5815/ijigsp.2014.07.02


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