Mathematical modeling for contour identification based on medicinal leaves and GIS images

• Main Authors: Chua, Lee Suan, Alias, Norma, Januari, Ristian, Mustaffa, Maizatul Nadirah, Ali, Akhtar, Ahmad Kamal, Mohamad Hidayad, Hayat, Imran
• Format: Article
• Language: English
• Published: Penerbit UTM Press 2016
• Subjects: Q Science; TP Chemical technology
• Online Access: http://eprints.utm.my/id/eprint/66818/1/NormaAlias2016_MathematicalModelingforContourIdentification.pdf; http://eprints.utm.my/id/eprint/66818/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006035824&doi=10.11113%2fjt.v78.10142&partnerID=40&md5=7982fc7029d558a99398d513f8d160ac

In this paper, the identification of contour medicinal leaves and GIS images has been determined. The purposes of the Geodesic Active Contour-Additive Operating Splitting (GAC-AOS) modelling are to identify an unknown type of medicinal leaves and edge detection of our images. Besides, three iterative methods such as SOR, RBGS and Jacobi method are used to solve the linear system of equations. In the implementation of the GAC-the AOS model, the experimental result demonstrates that the SOR method gives the best performance compared to the other two methods. The computation platform is based on Intel® CoreTM Duo Processor Architecture with MATLAB version R2011a. The performance analysis is based on the iteration numbers, execution time, accuracy and RMSE.