@article{li_non-contact_2023,
	title = {Non-contact clothing anthropometry based on two-dimensional image contour detection and feature point recognition},
	volume = {74},
	issn = {12225347},
	url = {http://revistaindustriatextila.ro/images/2023/1/009%20YUZHUO%20LI%20INDUSTRIA%20TEXTILA%20no.1_2023.pdf},
	doi = {10.35530/IT.074.01.202279},
	abstract = {Developing the technology of estimating human body size from two-dimensional images is the key to realising more
digitalization and artificial intelligence in the textile and garment industry. Therefore, this paper is an in-depth study of
estimating body sizes from two-dimensional images in a self-collected database of human body samples. First, the
artificial thresholds in the Canny edge operator were replaced by adaptive thresholds. The improved Canny edge
operator was combined with mathematical morphology so that it could detect a clear and complete single human
contour. Then a joint point detection algorithm based on a convolution neural network and human proportion is
proposed. It can detect human feature points with different body proportions. Finally, front and side images and manual
body measurements of 122 males aged 18–22 years were collected as the human sample database, calculating the
length and fit of the girth size. Compared with manual body measurement data, the error of human length and girth size
parameters within the national standard range of –1.5 {\textasciitilde} 1.5 cm can reach 91\% on average. This study provides an
accurate and convenient anthropometric method for digital garment engineering, which can be used for online shopping
and garment customization, and has a certain practical value.},
	number = {01},
	urldate = {2023-03-02},
	journal = {Industria Textila},
	author = {Li, Yuzhuo and Jiang, Lei and Li, Xinrong and Feng, Wenqian},
	month = feb,
	year = {2023},
	pages = {67--73},
}