Automatic Estimation of Body Measurements to Extract the Size and Body Shape 
Mong Hien Thi Nguyen1, Minh Hieu Tran2
1Mong Hien Thi Nguyen*, Department of Textile-Garment Engineering, Ho Chi Minh City University of Technology Faculty of Mechanical Engineering, Vietnam.
2Minh Hieu Tran, Department of Electric-Telecommunication Electronic Technologies in Ho Chi MInh City Technical and Economic College, Vietnam.
Manuscript received on November 14, 2021. Revised Manuscript received on November 18, 2021. Manuscript published on December 30, 2021. | PP: 24-28 | Volume-11 Issue-2, December 2021. | Retrieval Number: 100.1/ijeat.B32621211221 | DOI: 10.35940/ijeat.B3262.1211221
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper presents the research results of automatic estimation of the neck girth and inside leg to extract the size and body shape from the male sizing system table. The data used in the study is the 3D scan file *.obj from the 3D body scanner. The author uses the interpolation and optimization method in the algorithm to automatically extract 2 primary dimensions combined with the fuzzy logic method to extract sizes, body shapes. Besides, rotate matrix method combines with the optimal function used to write an algorithm to estimate the neck girth, inside leg measurements. Furthermore, a simple approach based on vertices and surface normal vectors data and optimal search was adapted to estimate the neck girth and inside leg measurements. These extraction results will be linked to the algorithm of the fuzzy logic to run for the automated process. This automatic algorithm will be very useful in face-to-face clothing purchases or online or for garment manufacturers in reducing shopping time and choosing sizes to design samples for customers.
Keywords: Algorithm, Fuzzy Logic, Automatic estimation, Extract the size, 3D body scanner.
Scope of the Article: Network Traffic Characterization and Measurements.