Dependence in Classification of Aluminium Waste

[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%.

[发布机构] Jurusan Matematika FMIPA Universitas Sriwijaya, Jl. Raya Palembang-Prabumulih Km.32, Inderalaya, Ogan Ilir, Sumatera Selatan; 30662, Indonesia^1

[效力级别] 化学

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