An Automatic Detection Method of Nanocomposite Film Element Based on GLCM and Adaboost M1. (6th September 2015)

• Record Type: Journal Article
• Authors: Guo, Hai; Yin, Jinghua; Zhao, Jingying; Liu, Yuanyuan; Yao, Lei; Xia, Xu
• Other Names: Chen Cheng-Fu Academic Editor.
• Is Part Of: Advances in materials science and engineering. Volume 2015(2015)
• Publication Date: 2015-09-06
• Subjects: Materials science -- Periodicals; Materials science; Periodicals; 620.11
• DOI: 10.1155/2015/205817
• Languages: English
• ISSNs: 1687-8434

Abstract

Abstract : An automatic detection model adopting pattern recognition technology is proposed in this paper; it can realize the measurement to the element of nanocomposite film. The features of gray level cooccurrence matrix (GLCM) can be extracted from different types of surface morphology images of film; after that, the dimension reduction of film can be handled by principal component analysis (PCA). So it is possible to identify the element of film according to the Adaboost M1 algorithm of a strong classifier with ten decision tree classifiers. The experimental result shows that this model is superior to the ones of SVM (support vector machine), NN and BayesNet. The method proposed can be widely applied to the automatic detection of not only nanocomposite film element but also other nanocomposite material elements.