Dynamic Reconfiguration of Active Net Structure for Region Extraction
Summary :
Active net is a deformable model which utilizes the network analogy of a physical region. In the model, the region of a target is detected by minimizing the energy defined for the sample points of the model. The region of the target is extracted using fixed network topology in the orginally proposed algorithm. In this paper, we introduce the network reconfiguration mechanisms such as tearing and division to realize multiple objects detection and complex object detecion. The introduced algorithm dynamically unlinks the arcs of the network when their strain value exceeds predefined threshold level. In the method, we propose a new image energy which improves the position sensitivity of edges without increasing computation cost. Experimental results for images taken by video camera show the validity of our approach.
- Publication
- IEICE TRANSACTIONS on Information Vol.E78-D No.10 pp.1288-1294
- Publication Date
- 1995/10/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Image Processing, Computer Graphics and Pattern Recognition
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Kazuyoshi YOSHINO, Satoru MORITA, Toshio KAWASHIMA, Yoshinao AOKI, "Dynamic Reconfiguration of Active Net Structure for Region Extraction" in IEICE TRANSACTIONS on Information,
vol. E78-D, no. 10, pp. 1288-1294, October 1995, doi: .
Abstract: Active net is a deformable model which utilizes the network analogy of a physical region. In the model, the region of a target is detected by minimizing the energy defined for the sample points of the model. The region of the target is extracted using fixed network topology in the orginally proposed algorithm. In this paper, we introduce the network reconfiguration mechanisms such as tearing and division to realize multiple objects detection and complex object detecion. The introduced algorithm dynamically unlinks the arcs of the network when their strain value exceeds predefined threshold level. In the method, we propose a new image energy which improves the position sensitivity of edges without increasing computation cost. Experimental results for images taken by video camera show the validity of our approach.
URL: https://global.ieice.org/en_transactions/information/10.1587/e78-d_10_1288/_p
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@ARTICLE{e78-d_10_1288,
author={Kazuyoshi YOSHINO, Satoru MORITA, Toshio KAWASHIMA, Yoshinao AOKI, },
journal={IEICE TRANSACTIONS on Information},
title={Dynamic Reconfiguration of Active Net Structure for Region Extraction},
year={1995},
volume={E78-D},
number={10},
pages={1288-1294},
abstract={Active net is a deformable model which utilizes the network analogy of a physical region. In the model, the region of a target is detected by minimizing the energy defined for the sample points of the model. The region of the target is extracted using fixed network topology in the orginally proposed algorithm. In this paper, we introduce the network reconfiguration mechanisms such as tearing and division to realize multiple objects detection and complex object detecion. The introduced algorithm dynamically unlinks the arcs of the network when their strain value exceeds predefined threshold level. In the method, we propose a new image energy which improves the position sensitivity of edges without increasing computation cost. Experimental results for images taken by video camera show the validity of our approach.},
keywords={},
doi={},
ISSN={},
month={October},}
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TY - JOUR
TI - Dynamic Reconfiguration of Active Net Structure for Region Extraction
T2 - IEICE TRANSACTIONS on Information
SP - 1288
EP - 1294
AU - Kazuyoshi YOSHINO
AU - Satoru MORITA
AU - Toshio KAWASHIMA
AU - Yoshinao AOKI
PY - 1995
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E78-D
IS - 10
JA - IEICE TRANSACTIONS on Information
Y1 - October 1995
AB - Active net is a deformable model which utilizes the network analogy of a physical region. In the model, the region of a target is detected by minimizing the energy defined for the sample points of the model. The region of the target is extracted using fixed network topology in the orginally proposed algorithm. In this paper, we introduce the network reconfiguration mechanisms such as tearing and division to realize multiple objects detection and complex object detecion. The introduced algorithm dynamically unlinks the arcs of the network when their strain value exceeds predefined threshold level. In the method, we propose a new image energy which improves the position sensitivity of edges without increasing computation cost. Experimental results for images taken by video camera show the validity of our approach.
ER -
English
