Verification Of Cross-sectional Shapes For Non-contact Measurements

In the continuous development and application of non-contact anthropometry technology,the development and improvement of today,the apparel industry has gradually been to intelligent,digital manufacturing as one direction.As people continue to pursue the fit of clothing comfort,the private custom industry gradually penetrate the market and loved by people.The past manual measurement of the human body has its limitations,time-consuming and can not reflect the human body three-dimensional graphics.The emerging non-contact measurement technology can generate hundreds of body size data and three-dimensional point cloud images on a human body in a very short time.Through the observation of graphics can be clearly and intuitively see the body's three-dimensional parts.Garment production based on this technology for personal customization can achieve better fit and comfort.However,with the continuous development of the non-contact measurement technology,the accuracy and accuracy of the measured data and the generated three-dimensional point cloud are constantly challenged and questioned.If the dimensional data and the graphic data obtained by a three-dimensional body scanning system are incorrect,then it is impossible to measure even more human body parts.And is discouraging many apparel companies due to their poorer accuracy and higher acquisition costs.This dissertation is based on the non-contact measurement technique,taking the chest cross-sectional pattern as the research object,and establishes the standard chest curve model and the non-contact measurement chest curve model respectively.The ultimate goal is to find a way to validate non-contact measurement pattern data.By verifying the model to verify the figure,a non-contact measurement pattern verification path is explored to provide a method for pattern verification.The specific research contents and conclusionsare as follows:(1)Anthropometric experimental design and data analysis: 210 unmarried young women aged from 18 to 25 years were chosen as experimental samples,and manual anthropometric and non-contact anthropometric measurements were performed using the same field collection.Measure the height,bust,waist and hip of young women by manual measurement.Whole-scan size acquisition of the same sample with Size Stream non-contact measurement system.Obtain manual measurement data and automatic measurement data respectively.And have a simple data analysis.(2)K-means body type cluster analysis: Multivariate correlation analysis and K-means body type clustering analysis were performed on the height,chest circumference,waist circumference,hip circumference,hip circumference,and body mass index.Body size index with significant correlation was chosen as the basis for body size clustering analysis.In order to determine the proportion of the largest body type.In the later study,the largest proportion of the chest shape extraction and model building.(3)Constructing a mathematical model of the standard bust curve of female body:Standard chest curve graph generation and model building based on manual measurement data.A manual measurement method was used to collect chest size data from 56 young women of 160/84 A.The initial point coordinates for mathematical modeling are obtained by Mat Lab software and the initial point coordinates are averaged.Curve fitting and smooth curve using Auto CAD software.Obtain equidistant points for the coordinates of the chest curve fitting point.Fit the curve with Mat Lab programming software to get the standard chest curve model.Finally,the quartic polynomial was selected to model the precordial curve.The cubic and quadratic polynomials were chosen to model the posterior breast curve.And the mathematical model is validated.(4)Build a non-contact measurement of chest curve mathematical model: Bust curve graph generation and model construction to be validated based on non-contact measurement data.In the graphical mathematical interface of Size Stream,the extraction of chest eigenvalues was performed on 49 160/84 A female bodies.Using Corel DRAW software to process.dxf format files.Using Auto CAD software smooth circle curve.To obtain equidistant points for the coordinates of the chest curve fitting point.Fitting curve with Mat Lab programming software to get non-contact measurement of chest curve model.Finally,the quartic polynomial was selected to model the precordial curve.The cubic andquadratic polynomials were chosen to model the posterior breast curve.And the mathematical model is validated.(5)Non-contact measurement of chest curve graphic verification: Automated data validation was performed using two methods based on the bust file difference and the SPSS paired sample T-test.Graphical verification is performed by a method based on summing the area of the curve graph.The resulting chest and posterior splines are stacked together using Mat Lab software.By calculating the area after the graphic overlay to determine whether the graph is available.The difficulty of this method is to determine the critical value of the stacking area.This paper selects the chest width,chest thickness of the file to determine the superposition of the threshold value.(6)Model verification and feasibility analysis: Five samples were randomly selected to validate the method.The validity of the model and the practicability of the graphical verification method are proved.The result shows that Size Stream non-contact measurement system can better reflect the human body brim cross-section curve graphics.However,some measurement errors still need to be updated to meet the market demand.The research of this subject has verified the automatic measurement of graphic data.Explored a non-contact measurement graphics verification path that solved the problem of not being able to validate the value of the graphics data.It provides reference for the accuracy and accuracy of automatic measurement of system data,and provides basic work for the development and improvement of non-contact measurement systems at home and abroad.