IEICE TRANSACTIONS on Information
Combined Detection Method in a Sea Surveillance System
Summary :
We propose a sea surveillance system that automatically detects intruding objects in the sea. The difficulty with an automatic system is detecting objects such as moving boats while reducing false positives caused by some waves and reflections in the sea. A false positive is reporting an object which doesn't actually exist, while a false negative is a failure in detecting an intruding object. Firstly, we identify factors of false positives. Secondly, we propose a new surveillance system considering these factors. Our proposed system combines three detecting methods. The first method is detection of Differences between Surveillance images and Flapping Reference images (DSFR). The second method is detection of Contours from Averaging images (CA). The third method is Silhouette object Detection (SD). The combination of DSFR and CA detects various moving objects under normal light conditions, while SD detects objects under backlight conditions. Finally we apply our proposed method to actual situations. Our proposed method detected boats while reducing false positives effectively.
- Publication
- IEICE TRANSACTIONS on Information Vol.E88-D No.2 pp.230-238
- Publication Date
- 2005/02/01
- Publicized
- Online ISSN
- DOI
- 10.1093/ietisy/e88-d.2.230
- Type of Manuscript
- PAPER
- Category
- Pattern Recognition
Authors
Keyword
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Kazuya TAKAHASHI, Yoshiki KOBAYASHI, Miyuki FUJII, Naoyuki SHIMBO, Hirotada UEDA, Kazuo TSUTSUI, "Combined Detection Method in a Sea Surveillance System" in IEICE TRANSACTIONS on Information,
vol. E88-D, no. 2, pp. 230-238, February 2005, doi: 10.1093/ietisy/e88-d.2.230.
Abstract: We propose a sea surveillance system that automatically detects intruding objects in the sea. The difficulty with an automatic system is detecting objects such as moving boats while reducing false positives caused by some waves and reflections in the sea. A false positive is reporting an object which doesn't actually exist, while a false negative is a failure in detecting an intruding object. Firstly, we identify factors of false positives. Secondly, we propose a new surveillance system considering these factors. Our proposed system combines three detecting methods. The first method is detection of Differences between Surveillance images and Flapping Reference images (DSFR). The second method is detection of Contours from Averaging images (CA). The third method is Silhouette object Detection (SD). The combination of DSFR and CA detects various moving objects under normal light conditions, while SD detects objects under backlight conditions. Finally we apply our proposed method to actual situations. Our proposed method detected boats while reducing false positives effectively.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e88-d.2.230/_p
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@ARTICLE{e88-d_2_230,
author={Kazuya TAKAHASHI, Yoshiki KOBAYASHI, Miyuki FUJII, Naoyuki SHIMBO, Hirotada UEDA, Kazuo TSUTSUI, },
journal={IEICE TRANSACTIONS on Information},
title={Combined Detection Method in a Sea Surveillance System},
year={2005},
volume={E88-D},
number={2},
pages={230-238},
abstract={We propose a sea surveillance system that automatically detects intruding objects in the sea. The difficulty with an automatic system is detecting objects such as moving boats while reducing false positives caused by some waves and reflections in the sea. A false positive is reporting an object which doesn't actually exist, while a false negative is a failure in detecting an intruding object. Firstly, we identify factors of false positives. Secondly, we propose a new surveillance system considering these factors. Our proposed system combines three detecting methods. The first method is detection of Differences between Surveillance images and Flapping Reference images (DSFR). The second method is detection of Contours from Averaging images (CA). The third method is Silhouette object Detection (SD). The combination of DSFR and CA detects various moving objects under normal light conditions, while SD detects objects under backlight conditions. Finally we apply our proposed method to actual situations. Our proposed method detected boats while reducing false positives effectively.},
keywords={},
doi={10.1093/ietisy/e88-d.2.230},
ISSN={},
month={February},}
Copy
TY - JOUR
TI - Combined Detection Method in a Sea Surveillance System
T2 - IEICE TRANSACTIONS on Information
SP - 230
EP - 238
AU - Kazuya TAKAHASHI
AU - Yoshiki KOBAYASHI
AU - Miyuki FUJII
AU - Naoyuki SHIMBO
AU - Hirotada UEDA
AU - Kazuo TSUTSUI
PY - 2005
DO - 10.1093/ietisy/e88-d.2.230
JO - IEICE TRANSACTIONS on Information
SN -
VL - E88-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2005
AB - We propose a sea surveillance system that automatically detects intruding objects in the sea. The difficulty with an automatic system is detecting objects such as moving boats while reducing false positives caused by some waves and reflections in the sea. A false positive is reporting an object which doesn't actually exist, while a false negative is a failure in detecting an intruding object. Firstly, we identify factors of false positives. Secondly, we propose a new surveillance system considering these factors. Our proposed system combines three detecting methods. The first method is detection of Differences between Surveillance images and Flapping Reference images (DSFR). The second method is detection of Contours from Averaging images (CA). The third method is Silhouette object Detection (SD). The combination of DSFR and CA detects various moving objects under normal light conditions, while SD detects objects under backlight conditions. Finally we apply our proposed method to actual situations. Our proposed method detected boats while reducing false positives effectively.
ER -
English
