Moments Added Statistical Shape Model for Boundary Extraction
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.
- Publication
- IEICE TRANSACTIONS on Information Vol.E92-D No.12 pp.2524-2526
- Publication Date
- 2009/12/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E92.D.2524
- Type of Manuscript
- LETTER
- Category
- Pattern Recognition
Authors
Keyword
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Haechul CHOI, Ho Chul SHIN, Si-Woong LEE, Yun-Ho KO, "Moments Added Statistical Shape Model for Boundary Extraction" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 12, pp. 2524-2526, December 2009, doi: 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.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.2524/_p
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@ARTICLE{e92-d_12_2524,
author={Haechul CHOI, Ho Chul SHIN, Si-Woong LEE, Yun-Ho KO, },
journal={IEICE TRANSACTIONS on Information},
title={Moments Added Statistical Shape Model for Boundary Extraction},
year={2009},
volume={E92-D},
number={12},
pages={2524-2526},
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.},
keywords={},
doi={10.1587/transinf.E92.D.2524},
ISSN={1745-1361},
month={December},}
Copy
TY - JOUR
TI - Moments Added Statistical Shape Model for Boundary Extraction
T2 - IEICE TRANSACTIONS on Information
SP - 2524
EP - 2526
AU - Haechul CHOI
AU - Ho Chul SHIN
AU - Si-Woong LEE
AU - Yun-Ho KO
PY - 2009
DO - 10.1587/transinf.E92.D.2524
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2009
AB - 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.
ER -
English
