Department of Textile Engineering, Faculty of Engineering, Yazd University, Yazd, Iran
Abstract
Classification of different types of human body by adoption of meaningful rules obtained from data analysis of different parts of the body is very important as it is applied in many scientific methods. Applying data mining techniques on the obtained data and extraction of their meaningful rules could be helpful for different types of classification and ultimate determination of the garment of sizing system. It is important to note that recognition of differences in human body shape groupings and extraction of significant dimensional body variability can be used by dress designers and clothing manufacturers. In this study 10 body parts of 2002 Iranian men of 18 to 30 years old were measured for their body shape determination. In this study, factor analysis was employed to extract important variables and K-means clustering for body shape grouping. The obtained data were categorized into four groups of men's clothing sizes.
Shamsaei, R., Payvandy, P., & Fattahi, S. (2013). Factorial Analysis and K-Means Clustering Methods for Extraction of Human Body Size Parameters and Shape Groupings. Journal of Textile Science and Technology, 3(3), 11-16.
MLA
R. Shamsaei; P. Payvandy; S. Fattahi. "Factorial Analysis and K-Means Clustering Methods for Extraction of Human Body Size Parameters and Shape Groupings". Journal of Textile Science and Technology, 3, 3, 2013, 11-16.
HARVARD
Shamsaei, R., Payvandy, P., Fattahi, S. (2013). 'Factorial Analysis and K-Means Clustering Methods for Extraction of Human Body Size Parameters and Shape Groupings', Journal of Textile Science and Technology, 3(3), pp. 11-16.
VANCOUVER
Shamsaei, R., Payvandy, P., Fattahi, S. Factorial Analysis and K-Means Clustering Methods for Extraction of Human Body Size Parameters and Shape Groupings. Journal of Textile Science and Technology, 2013; 3(3): 11-16.
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