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Journal Article Moments Added Statistical Shape Model for Boundary Extraction
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Authors
Hae Chul CHoi, Ho Chul Shin, Si Woong Lee, Yun Ho Ko
Issue Date
2009-12
Citation
IEICE Transactions on Information and Systems, v.E92-D, no.12, pp.2524-2526
ISSN
0916-8532
Publisher
일본, 전자정보통신학회 (IEICE)
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1587/transinf.E92.D.2524
Abstract
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. Copyright © 2009 The Institute of Electronics, Information and Communication Engineers.
KSP Keywords
Differential equation, Extraction method, Information and communication, Low-quality image, Point distribution model(PDM), Statistical characteristics, boundary extraction, simulation results, statistical shape model, training set