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Although a laser profile sensor (LPS) can be used to measure dimensions, the “shadow region” generally degrades the accuracy and precision of width measurements. The accuracy and precision of such measurements should be improved.

In this paper, the authors propose herein a technique that combines high dynamic range (HDR) imaging with logistic fitting. First, a HDR image is composed of several images acquired with different exposure times, which augments the grayscale of the object profile and significantly reduces overexposure. Next, the profile is fit to a logistic function, which provides accurate and precise edge coordinates. Finally, given the edge coordinates, the object width is calculated.

To verify the stability of this logistic algorithm, the authors simulate different noise conditions and different degrees of incomplete edge data. In addition, the progressiveness of the algorithm is demonstrated by comparing the results with those of other algorithms and with the height measurement. Furthermore, the suitability of the system is verified experimentally.

Because of the limitation of the condition of laboratory, in the experimental section, this paper cannot represent perfectly the industrial situation. It makes this section limited in demonstration.

In this paper, the results show that the measurement accuracy and precision of the width is improved and exceeds that of the height measurement. The proposed HDR imaging method with logistic fitting may be applied to LPS width measurements, which should significantly aid the development of LPSs.

The purpose of this study is to investigate the shape change of breast during movement to inform product development of bras and other female wearable products.

Using the latest 4D body scanning technology, the authors monitored the change of seven non-circumferential breast measurements, including four linear measurements (widths, depth, etc.) and three angular measurements, across nine dynamic scans of a complete gait cycle during running. A series of statistical analysis were conducted to thoroughly investigate the measurement values in dynamic states compared with values extracted from static 3D scans.

Major findings are as follows: (1) For width-underbust, chest-depth, vertical-acromion and angle ABD, more than half of the dynamic frames presents a significant difference with the static frame. (2) Width-underbust and chest-depth measured in static can underestimate the actual values under motion. (3) vertical-acromion presents a W-shaped general trend for the nine dynamic frames with peaks observed at the keyframes (i.e. when a participant's right or left knee bends the most and rises to its highest level) and lows at the intermediate frames. (4) Angle ABD and angle BAD both present an M-shaped general trend, the exact opposite of a W-shaped trend.

While 3D body scanning and motion capture systems have both contributed significantly to the study of breast, 4D body scanning incorporates the advantages of both technologies and captures the 3D surface of the body during movement at each instant moment. This is one of the first studies that adopt the new technology for apparel applications.

The hygroscopic properties of 3D-printed filaments and moisture absorption itself during the process result in dimensional inaccuracy, particularly for nozzle movement along the x-axis and for micro-scale features. In view of that, this study aims to analyze in depth the dimensional errors and deviations of the fused filament fabrication (FFF)/fused deposition modeling (FDM) 3D-printed micropillars (MPs) from the reference values. A detailed analysis into the variability in printed dimensions below 1 mm in width without any deformations in the printed shape of the designed features, for challenging filaments like polymethyl methacrylate (PMMA) has been done. The study also explores whether the printed shape retains the designed structure.

A reference model for MPs of width 800 µm and height 2,000 µm is selected to generate a g-code model after pre-processing of slicing and meshing parameters for 3D printing of micro-scale structure with defined boundaries. Three SETs, SET-A, SET-B and SET-C, for nozzle diameter of 0.2 mm, 0.25 mm and 0.3 mm, respectively, have been prepared. The SETs containing the MPs were fabricated with the spacing (S) of 2,000 µm, 3,200 µm and 4,000 µm along the print head x-axis. The MPs were measured by taking three consecutive measurements (top, bottom and middle) for the width and one for the height.

The prominent highlight of this study is the successful FFF/FDM 3D printing of thin features (<1mm) without any deformation. The mathematical analysis of the variance of the optical microscopy measurements concluded that printed dimensions for micropillar widths did not vary significantly, retaining more than 65% of the recording within the first standard deviation (SD) (±1 s). The minimum value of SD is obtained from the samples of SET-B, that is, 31.96 µm and 35.865 µm, for height and width, respectively. The %RE for SET-B samples is 5.09% for S = 2,000µm, 3.86% for S = 3,200µm and 1.09% for S = 4,000µm. The error percentage is so small that it could be easily compensated by redesigning.

The study does not cover other 3D printing techniques of additive manufacturing like stereolithography, digital light processing and material jetting.

The presented study can be potentially implemented for the rapid prototyping of microfluidics mixer, bioseparator and lab-on-chip devices, both for membrane-free bioseparation based on microfiltration, plasma extraction from whole blood, size-selection trapping of unwanted blood cells, and also for membrane-based plasma extraction that requires supporting microstructures. Our developed process may prove to be far more economical than the other existing techniques for such applications.

For the first time, this work presents a comprehensive analysis of the fabrication of micropillars using FDM/FFF 3D printing and PMMA in filament form. The primary focus of the study is to minimize the dimensional inaccuracies in the 3D printed devices containing thin features, especially in the area of biomedical engineering, by delivering benefits from the choice of the parameters. Thus, on the basis of errors and deviations, a thorough comparison of the three SETs of the fabricated micropillars has been done.

Accurately, positioning is a fundamental requirement for vision measurement systems. The calculation of the harvesting width can not only help farmers adjust the direction of the intelligent harvesting robot in time but also provide data support for future unmanned vehicles.

To make the length of each pixel equal, the image is restored to the aerial view in the world coordinate system. To solve the problem of too much calculation caused by too many particles, a certain number of particles are scattered near the crop boundary and the distribution regularities of particles’ weight are analyzed. Based on the analysis, a novel boundary positioning method is presented. In the meantime, to improve the robustness of the algorithm, the back-projection algorithm is also used for boundary positioning.

Experiments demonstrate that the proposed method could well meet the precision and real-time requirements with the measurement error within 55 mm.

In visual target tracking, using particle filtering, a rectangular is used to track the target and cannot obtain the boundary information. This paper studied the distribution of the particle set near the crop boundary and proposed an improved particle filtering algorithm. In the algorithm, a small amount of particles is used to determine the crop boundary and accurate positioning of the crop boundary is realized.

The purpose of this paper is to focus on how to automatically generate the individualized patterns for women’s suits based on the 3D body point-cloud images.

With the software Imageware, the point-cloud data of the female body were measured according to the female body feature to obtain the heights, widths, depths and girths at various landmarks. Then the relationship between the height of each landmark and the body height was analyzed to build the height calculation rules by software SPSS, and the prediction models of body girths were established from the body widths and depths using regression analysis for pattern generation.

The pattern generation rules were built with the relationships between a human body and the garment patterns using the graphic flattening method. Based on the above rules, the final patterns were drafted automatically by using these dimensions to fit the subjects. The try-on experiment also showed that the individualized suits could fit the subjects’ body well at some feature landmarks.

In order to realize tailor-made and meet the consumers’ demands for individualized clothes, the development of garment CAD system has become inevitable in the garment industry. This paper could provide the foundation for automatic pattern generation, and technical support for tailor-made.

This paper (which is the first of three) explains how to undertake an anthropometric survey, first, by reviewing previous surveys and size charts to select which measurements to take and the appropriate equipment. The sample of persons to be measured had to be determined, the main constraint being the availability of time. The selection of measurements was made for the end use of constructing garment patterns by both direct and proportional measurement systems. ‘Check’ measurements for accuracy were also built into the procedure. Finally 10 measurements were selected and 100 young women between the ages of 18 and 28 years were measured. It is concluded that measuring the human body is not easy. Hopefully new technology will improve this task. Twenty more body measurements will be brought into use, which will be explained in Part 2.

The purpose of this study was to categorize the whole body shapes of overweight and obese females in the US and examine apparel fit based on the current ASTM sizing standards related to the body shapes categorized.

Body scan data from 2,672 subjects were used. To categorize their whole body shapes using 97 body measurements, principal component analysis with varimax rotation, a hierarchical cluster analysis and K-means cluster analysis were used. To compare the ASTM sizing standards for plus sizes (curvy and straight) and missy sizes (curvy and straight), five body parts (bust, under bust, waist, top hip, hip) using the formula for fit tolerance (measurement plus half of the interval) were compared with the ASTM sizing standards to determine the size appropriate for each body part.

Five whole body shapes among overweight and obese females in the US were categorized: Rectangle-curvy; parallelogram-moderately curvy; parallelogram-hip tilt; inverted trapezoid-moderately curvy and inverted trapezoid-hip tilt. When the body measurements in each body shape were compared with the current ASTM sizing systems for both misses and plus sizes, four-fifths or more of overweight and obese female adults in the US would find it difficult to obtain a perfect fit for both tops and bottoms.

Identifying whole body shapes among overweight and obese women in the US contributes significantly, as it will help apparel companies that target the markets of larger women develop a new sizing system. This study is the first attempt to analyze fit by comparing the ASTM sizing charts with body measurements in each body shape group. Further, the study contributes to the body-related literature by filling gaps in missing whole BS categories among overweight and obese females.

Identification of human body shapes has been a key issue to develop sizing standards for ready‐to‐wear and to develop made‐to‐measure applications. Current methods to identify the body shapes are mostly based on subjective/visual determination approaches. The purpose of this paper is to look for numerical evaluation parameters for an objective method in order to classify the body shapes and to build up an automated process link.

Female subjects were chosen for the experimental design. 3D body scanning technology was integrated in the process for measurement taking and body silhouette detection of the sample group. Based on this sample data set, body shape identification was realized by referees as visual analyses, and additionally, an objective method was tried out by using body dimensions as numerical evaluation parameters. Obtained results with the sample group were inserted in a database and a body shape calculation tool was developed.

Statistical analyses showed that there is mostly a good agreement between the pairs of the evaluations including the objective calculation methods and the subjective assessments of the referees. The calculation tool was designed as web‐based software in order to integrate with further developments and automation purposes.

A new automatic tool was developed to make the body shape classification objective and repeatable. By integrating this tool to the product development chain, a continuous process link can be provided for the companies through the way for better fitting clothing.

With the rapid advancement of computer information technology, the traditional clothing industry has stridden towards automation and digitization that drive the growth of electronic commerce and line retailing. The purpose of this paper is to propose an approach on 3D upper body modelling based on the body measurements extracted by non-contact anthropometry.

Based on the frontal and side images of the human body, the body sizes were extracted through silhouette extraction, identification of landmarks and girth prediction. The generation rules of 15 characteristic cross-sectional curves were established using a method “feature points – inserted points – feature curves – basic surface – mannequin”. The feature points of each position were determined at each curve, such as the side neck point, front neck point, shoulder point, bust point, and bust root point and so on to get the cross-sections, and then some feature points were inserted at the curves according to the widths and depths to establish the calculative models. For example, there are 18 points distributed at the bust cross-sectional curve to determine the shape.

The final mannequin could describe the basic characteristics of a human body, and the shape of the feature curves could also fit the body type to provide basis for the future research on automatic pattern generation.

This study can realize the 3D virtual modelling of female upper body and the automatic generation of the individualized apparel patterns based on the frontal and side images.

Two-dimensional (2D) measurement technology has become more popular than before, thanks to the widespread availability of smartphones and smart devices. However, most existing 2D body measurement systems have background constraints and may raise privacy concerns. The purpose of this research was to test the idea of designing a 2D measurement system that works with a color-coded measurement garment for background removal and privacy protection. Clothing consumers can use the proposed system for daily apparel shopping purposes.

A 2D body measurement system was designed and tested. The system adopted a close-fitted color-coded measurement garment and used neural network models to detect the color-code in the garment area and remove backgrounds. In total, 78 participants were recruited, and the collected data were split into training and testing sets. The training dataset was used to train the neural network and statistical prediction models for the 2D system. The testing dataset was used to compare the performance of the 2D system with a commercial three-dimensional (3D) body scanner.

The results showed that the color-coded measurement garment worked well with the neural network models to process the images for measurement extraction. The 2D measurement system worked better at close-fitted areas than loose-fitted areas.

This research combined a color-coded measurement garment with neural network models to solve the privacy and background challenges of the 2D body measurement system. Other researchers have never studied this approach.