Details

Autor(en) / Beteiligte

• Bencherqui, Ahmed
• Karmouni, Hicham
• Daoui, Acharf
• Alfidi, Mohammed
• Qjidaa, Hassan
• Sayyouri, Mhamed

Titel

Optimization of Jacobi Moments Parameters using Artificial Bee Colony Algorithm for 3D Image Analysis

Ist Teil von

• 2020 Fourth International Conference On Intelligent Computing in Data Sciences (ICDS), 2020, p.1-7

Ort / Verlag

IEEE

Erscheinungsjahr

2020

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• In this article, we propose a new algorithm for the optimization of the parameters of Jacobi moments by artificial bee colony (ABC) algorithm for the analysis of 3D images. The ABC algorithm is used to select the optimal parameters \alpha and \beta of Jacobi polynomials and the optimal orders of Jacobi moments to improve the quality of 3D image reconstruction. The performance of the proposed algorithm is evaluated on 3D images using quantitative criteria such as the mean square error and peak signal-to-noise ratio. The results of simulations have shown the efficiency of the proposed algorithm for the analysis of 3D images compared to conventional methods.