An-Image Based Estimation System of Human body shape

• Main Authors: Yu-Hsien Liao, 廖育賢
• Other Authors: Sheng-Fuu Lin
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/68702458780889852341

碩士 === 國立交通大學 === 電機與控制工程系所 === 96 === The information of the waistline, chestline, shoulder width, and the length of legs are the essential information when buying clothes. The alvanscan system powered by intellifit is popularized gradually. However, this system works only in some certain place and its price is very expensive. Hence, a new image-based human body shape estimation system is described in this thesis. It can greatly reduce the cost of time and money. In this paper, the skin color region is first segmented by using skin color characteristic and morphology of image processing. Along with the edge detection and connectivity analysis, the correct human body region can be segmented by region growing and the naked parts of human body are marked. Next, the thickness of clothing is estimated by adopting fuzzy inference theorem. Using the body shape trained from the neural network, the real body shape under the clothing can be estimated and determined. The various width and length of human body can be calculated by Bezier curve finally. There are two main contributions in this thesis. First, the body shape under clothing can be estimated by using the proposed clothing thickness estimation system based on fuzzy inference system. Second, the various width and length of human body can be calculated while the information of particular frontal and lateral width is given. Then, the curves of a human can be simulated. From the experiment results, the human body width and length data for buying clothes can be obtained by using three images with fixed poses.