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The Pattern Segmentation of 3D Image Information Using FCM  

Kim Eun-Seok (제노시스)
Joo Ki-See (목포해양대학교)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.10, no.5, 2006 , pp. 871-876 More about this Journal
Abstract
In this thesis, to accurately measure 3D face information using the spatial encoding patterns, the new algorithm to segment the pattern images from initial face pattern image is proposed. If the obtained images is non-homogeneous texture and ambiguous boundary pattern, the pattern segmentation is very difficult. Furthermore. the non-encoded areas by accumulated error are occurred. In this thesis, the FCM(fuzzy c-means) clustering method is proposed to enhance the robust encoding and segmentation rate under non-homogeneous texture and ambiguous boundary pattern. The initial parameters for experiment such as clustering class number, maximum repetition number, and error tolerance are set with 2, 100, 0.0001 respectively. The proposed pattern segmentation method increased 8-20% segmentation rate with conventional binary segmentation methods.
Keywords
CNN; Tim3D face information; spatial encoding patterns; non-homogeneous texture; ambiguous boundary; FCM e-multiplexing; Pre.Post processor; OTA; Pipeline;
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