Material surfaces identification from photo images

Zainudin, Fathin Liyana and Mahamad, Abd Kadir and Saon, Sharifah and Zakaria, Rozana (2017) Material surfaces identification from photo images. In: Innovative Computational Methods of Acoustics Parameters. Penerbit UTM Press, pp. 47-57. ISBN 9789835214417

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Abstract

Absorption coefficient is one of an important feature in acoustic engineering. Different types of materials have different level of sound absorption. A few studies have been conducted in order to test different alternatives for identifying absorption coefficient of material surfaces (Yahya et al., 2012, Hodgson and Scherebnyj, 2006). In order to identify the surfaces absorption coefficient, the material surfaces need to be identified first. For material identification and classification, the surface texture is the key feature used for extraction. Texture analysis is one of the most important techniques used in image processing and pattern recognition. In texture analysis, the first and most important task is to extract texture features which efficiently embody information about the textural characteristics of the original image (Sujatha et al., 2012).These features can then be used for the description or classification of different texture images. Various algorithms have been put forward for texture analysis, such as the Gray Level Co-occurrence Matrix (GLCM) (Bridle, 1989), Gabor filtering, wavelet decomposition, modified Zernike moments (Sim et al., 2004) etc.

Item Type:Book Section
Subjects:Q Science > QA Mathematics > QA76 Computer software
Divisions:Faculty of Electrical and Electronic Engineering > Department of Computer Engineering
ID Code:10582
Deposited By:Mr. Mohammad Shaifulrip Ithnin
Deposited On:10 Oct 2018 15:53
Last Modified:10 Oct 2018 15:53

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