Title: Decision aid system for Omani medical herb leaves recognition using computer vision and artificial intelligence

Authors: Majed Bouchahma; Mohsin Al-Balushi; Sheikha Al-Hosni; Hamood Al Wardi

Addresses: Department of Information Technology, College of Applied Sciences, P.O. Box 10, P.C: 329 Rustaq, Sultanate of Oman; Laboratoire SIIVA, Institut Supérieur d'Informatique, Université de Tunis El Manar, Tunisia ' Department of Information Technology, College of Applied Sciences, P.O. Box 10, P.C: 329 Rustaq, Sultanate of Oman ' Department of Information Technology, College of Applied Sciences, P.O. Box 10, P.C: 329 Rustaq, Sultanate of Oman ' College of Applied Sciences, P.O. Box 10, P.C: 329 Rustaq, Sultanate of Oman

Abstract: Herbs have been widely used in food preparation, medicine and cosmetic industry. Knowing which herbs to be used would be very critical in these applications. This research aims to define a method to classify the herbs plants based on their leaves colours and shapes. An open source decision aid system is designed and developed especially for helping scientist. The proposed system employs artificial and image processing techniques to perform recognition on a number of Omani species of medical herbs.

Keywords: decision aid system; DAS; medical herbs; computer vision; artificial intelligence; speeded up robust features; SURF.

DOI: 10.1504/IJIDS.2019.101142

International Journal of Information and Decision Sciences, 2019 Vol.11 No.2, pp.129 - 140

Accepted: 16 Nov 2017
Published online: 22 Jul 2019 *

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