Moments Added Statistical Shape Model for Boundary Extraction

Haechul CHOI  Ho Chul SHIN  Si-Woong LEE  Yun-Ho KO  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E92-D   No.12   pp.2524-2526
Publication Date: 2009/12/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E92.D.2524
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Pattern Recognition
Keyword: 
boundary extraction,  statistical shape model,  moment,  

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Summary: 
In this paper, we propose a method for extracting an object boundary from a low-quality image such as an infrared one. To take full advantage of a training set, the overall shape is modeled by incorporating statistical characteristics of moments into the point distribution model (PDM). Furthermore, a differential equation for the moment of overall shape is derived for shape refinement, which leads to accurate and rapid deformation of a boundary template toward real object boundary. The simulation results show that the proposed method has better performance than conventional boundary extraction methods.