Dependence in Classification of Aluminium Waste

3rd International Conference on Science & Engineering in Mathematics, Chemistry and Physics 2015

数学;化学;物理学

Resti, Y.^1

Jurusan Matematika FMIPA Universitas Sriwijaya, Jl. Raya Palembang-Prabumulih Km.32, Inderalaya, Ogan Ilir, Sumatera Selatan

30662, Indonesia^1

关键词: Bayes' theorem;    Gaussian copula;    Image data;    Pure aluminium;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/622/1/012052/pdf
DOI  :  10.1088/1742-6596/622/1/012052

来源: IOP

【 摘 要 】

Based on the dependence between edge and colour intensity of aluminium waste image, the aim of this paper is to classify the aluminium waste into three types; pure aluminium, not pure aluminium type-1 (mixed iron/lead) and not pure aluminium type 2 (unrecycle). Principal Component Analysis (PCA) was employed to reduction the dimension of image data, while Bayes' theorem with the Gaussian copula was applied to classification. The copula was employed to handle dependence between edge and colour intensity of aluminium waste image. The results showed that the classifier has been correctly classifiable by 88.33%.