Abstract
In this fast-phased world, the fashion industry is changing and tries to give confidence to people who wear their clothes. The fit of the garment depends on accuracy of measurements. The traditional method of measuring may provide wrong information if the tools are inappropriate. Even though 3D body scanning can give accurate results, they cannot be afforded by small business setups. 3D imaging makes the process expensive. Not all can afford a stylish to measure and stitch 4–5 sets of outfits and select the best. The working community has no time to visit stores/tailoring shops regularly. This paper proposes inexpensive method for extracting human body measurements from 2D images which helps the society to reach out to the different styles and fitted garments of their taste. Human body measurements are extracted with the help of—Affine and Metric correction, Green Screen Segmentation, Heuristics for detection and pixel-to-real world distance. It is a 2D-image-based system which takes one front view, side view and front view with checkerboard. This method involves manual annotation technique.
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