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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.

The paper presents research to establish a simulation program on the Fuzzy logic for the Vietnamese women from 6-18 years old in Ho Chi Minh City. The author used across statistical method, component analysis method, factor analysis method, ANOVA by the SPSS software to overall test the difference between groups, and using the simulation by the Matlab software in this research. This research classified body shapes by a combination of 3 height groups, such as low, medium, and high. They combined with the FFIT and BMI standards to produce the final result of having all 27 women shapes. The results of the groups used to put into the Fuzzy logic simulation program by the Matlab software with the MISO model. It had five variables for inputs, and the output was the result of the shape which needed to know. This is scientific research, so it applies to teach subjects in the field of costume design. Besides, it supports businesses, and fashion designers will have a basis for advice on choosing costumes that fit the body shape, as well as the object of measurement, will have an objective awareness of body shapes to give training directions, adjust the physique appropriately.

Medical image fusion plays a great role in image processing because it can increase the visual interpretation of the medical images especially brain images. The images with low interpretation can have influence on diagnostic results because each small detail in medical images is a very important clue, which can help doctors find out a suitable treatment plan. In this paper, we proposed a method for medical image fusion especially brain magnetic resonance image (MRI). The histogram equalization is applied to enhance the contrast of MRI and then cross bilateral filter is used to extract detail images from the source images. The source images are fused by weighted average using the weights calculated from the detail images to make the image result with more information. Our proposed method is better than the other recent methods based on compared results.