To improve body-type classification research and personalized clothing, this study adopted a research method of “three-dimensional (3D) scanning + photos” for the body-shape classification of young females’ waist–abdomen–hip. A total of 178 female college students were recruited for manual, photo and 3D body measurement to get the main body information. Based on the data acquired from 3D scanning, the corresponding heights, angles and other parameters of the waist, abdomen and hip were selected and used to analyze the human body in two respects of shape and height. Then the body-shape indexes and the height indexes were respectively analyzed, and 16 shape characteristic indicators and four height characteristic parameters affecting the waist, abdomen and hip were extracted. Three types in shape and two types in height were obtained, and the main classification rules of the waist–abdomen–hip shape were also concluded to identify the body type based on the body measurements extracted from body photos, which realized the automatic body-type identification based on body photos. It was of great practical significance to provide a basis for personalized customization of fast clothing and the subdivision of the human body shape, which could meet the individual customer’s requirements.

This study proposed a method on how to obtain and predict body measurements from frontal and side images of a subject for the individualized pattern generation of women's pants. According to the relationship between front and back patterns and a body torso, 32 important pattern dimensions relevant to certain body dimensions were determined by the graphic flattening method. For the body dimensions (such as perimeters) that could not be directly extracted from the body images, the prediction models were established based on the available width and depth measurements. The body measurements from the body images of 425 subjects were compared with the corresponding manual measurements, which showed a good correlation between the automated and manual measurements. The tried-on test showed that the pants made with the generated patterns demonstrated good fitting effect at the important characteristic landmarks of a participating subject. This method can accelerate the pattern-making process for women's pants based on body measurements, reducing human efforts, costs and production time.

Female breasts are regarded as a factor reflecting women’s morphological beauty. An appropriate bra can fulfill aesthetic needs, thus boosting self-esteem. This study proposed a method to analyze young women’s breast-bra morphological variations between two identical bras with different bra cup thicknesses. The 3D surface scan data of 129 female students who were braless and wore a thin bra (13 mm) and a thick bra (23 mm) were analyzed. Integral sections of the breasts and bra were cut at a fixed thickness of 10 mm, and slice maps were derived. Morphological parameters were extracted in braless and the two bra conditions. The variations in breast-bra shape caused by different thicknesses of bra cups were evaluated by quantifying breast ptosis, gathering, and breast slice area. The results showed that the thin bra lifted the breasts by 2.16 cm, whereas the thick bra decreased breast separation, gathering the breasts and moving them 2.15 cm laterally towards the center of the chest wall. Moreover, prediction models constructed using the critical morphological parameters were used to characterize breast-bra shape after wearing the provided bras. The findings lay the groundwork for quantifying the breast-bra shape variation caused by different bra cup thicknesses, allowing young females to choose optimally fitting bras to achieve their desired breast aesthetics.