Water region detection supporting ship identification in port surveillance

Xinfeng Bao; Svitlana Zinger; Rob Wijnhoven; Peter H.N. De With

doi:10.1007/978-3-642-33140-4_39

Water region detection supporting ship identification in port surveillance

Xinfeng Bao, Svitlana Zinger, Rob Wijnhoven, Peter H.N. De With

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

9 Citations (Scopus)

1 Downloads (Pure)

Abstract

In this paper, we present a robust and accurate water region detection technique developed for supporting ship identification. Due to the varying appearance of water body and frequent intrusion of ships, a region-based recognition is proposed. We segment the image into perceptually meaningful segments and find all water segments using a sampling-based Support Vector Machine (SVM). The algorithm is tested on 6 different port surveillance sequences and achieves a pixel classification recall of 97.5% and precision of 96.4%. We also apply our water region detection to support the task of multiple ship detection. Combined with our cabin detector, it successfully removes 74.6% false detections generated in the cabin detection process. A slight decrease of 5% in the recall value is compensated by a significant improvement of 15% in precision.

Original language	English
Title of host publication	Advanced Concepts for Intelligent Vision Systems - 14th International Conference, ACIVS 2012, Proceedings
Pages	444-454
Number of pages	11
DOIs	https://doi.org/10.1007/978-3-642-33140-4_39 https://doi.org/10.1007/978-3-642-33140-4_39
Publication status	Published - 24 Sept 2012
Event	14th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS 2012) - Brno, Czech Republic Duration: 4 Sept 2012 → 7 Sept 2012 Conference number: 14 http://acivs.org/acivs2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7517 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	14th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS 2012)
Abbreviated title	AVICS 2012
Country/Territory	Czech Republic
City	Brno
Period	4/09/12 → 7/09/12
Internet address	http://acivs.org/acivs2012

Bibliographical note

Proceedings of the 14th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS), 4-7 September 2012, Brno, Czech Republic

Keywords

Autonomous Port Surveillance
Multiple Ship Detection
Water Detection

Access to Document

Cite this

Bao, X., Zinger, S., Wijnhoven, R., & De With, P. H. N. (2012). Water region detection supporting ship identification in port surveillance. In Advanced Concepts for Intelligent Vision Systems - 14th International Conference, ACIVS 2012, Proceedings (pp. 444-454). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7517 LNCS). https://doi.org/10.1007/978-3-642-33140-4_39, https://doi.org/10.1007/978-3-642-33140-4_39

Bao, Xinfeng ; Zinger, Svitlana ; Wijnhoven, Rob et al. / Water region detection supporting ship identification in port surveillance. Advanced Concepts for Intelligent Vision Systems - 14th International Conference, ACIVS 2012, Proceedings. 2012. pp. 444-454 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{4a632ea4b1d7437d8fd7af207c07c44b,

title = "Water region detection supporting ship identification in port surveillance",

abstract = "In this paper, we present a robust and accurate water region detection technique developed for supporting ship identification. Due to the varying appearance of water body and frequent intrusion of ships, a region-based recognition is proposed. We segment the image into perceptually meaningful segments and find all water segments using a sampling-based Support Vector Machine (SVM). The algorithm is tested on 6 different port surveillance sequences and achieves a pixel classification recall of 97.5% and precision of 96.4%. We also apply our water region detection to support the task of multiple ship detection. Combined with our cabin detector, it successfully removes 74.6% false detections generated in the cabin detection process. A slight decrease of 5% in the recall value is compensated by a significant improvement of 15% in precision.",

keywords = "Autonomous Port Surveillance, Multiple Ship Detection, Water Detection",

author = "Xinfeng Bao and Svitlana Zinger and Rob Wijnhoven and {De With}, {Peter H.N.}",

note = "Proceedings of the 14th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS), 4-7 September 2012, Brno, Czech Republic; 14th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS 2012), AVICS 2012 ; Conference date: 04-09-2012 Through 07-09-2012",

year = "2012",

month = sep,

day = "24",

doi = "10.1007/978-3-642-33140-4_39",

language = "English",

isbn = "9783642331398",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "444--454",

booktitle = "Advanced Concepts for Intelligent Vision Systems - 14th International Conference, ACIVS 2012, Proceedings",

url = "http://acivs.org/acivs2012",

}

Bao, X, Zinger, S, Wijnhoven, R & De With, PHN 2012, Water region detection supporting ship identification in port surveillance. in Advanced Concepts for Intelligent Vision Systems - 14th International Conference, ACIVS 2012, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7517 LNCS, pp. 444-454, 14th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS 2012), Brno, Czech Republic, 4/09/12. https://doi.org/10.1007/978-3-642-33140-4_39, https://doi.org/10.1007/978-3-642-33140-4_39

Water region detection supporting ship identification in port surveillance. / Bao, Xinfeng; Zinger, Svitlana; Wijnhoven, Rob et al.
Advanced Concepts for Intelligent Vision Systems - 14th International Conference, ACIVS 2012, Proceedings. 2012. p. 444-454 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7517 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Water region detection supporting ship identification in port surveillance

AU - Bao, Xinfeng

AU - Zinger, Svitlana

AU - Wijnhoven, Rob

AU - De With, Peter H.N.

N1 - Conference code: 14

PY - 2012/9/24

Y1 - 2012/9/24

N2 - In this paper, we present a robust and accurate water region detection technique developed for supporting ship identification. Due to the varying appearance of water body and frequent intrusion of ships, a region-based recognition is proposed. We segment the image into perceptually meaningful segments and find all water segments using a sampling-based Support Vector Machine (SVM). The algorithm is tested on 6 different port surveillance sequences and achieves a pixel classification recall of 97.5% and precision of 96.4%. We also apply our water region detection to support the task of multiple ship detection. Combined with our cabin detector, it successfully removes 74.6% false detections generated in the cabin detection process. A slight decrease of 5% in the recall value is compensated by a significant improvement of 15% in precision.

AB - In this paper, we present a robust and accurate water region detection technique developed for supporting ship identification. Due to the varying appearance of water body and frequent intrusion of ships, a region-based recognition is proposed. We segment the image into perceptually meaningful segments and find all water segments using a sampling-based Support Vector Machine (SVM). The algorithm is tested on 6 different port surveillance sequences and achieves a pixel classification recall of 97.5% and precision of 96.4%. We also apply our water region detection to support the task of multiple ship detection. Combined with our cabin detector, it successfully removes 74.6% false detections generated in the cabin detection process. A slight decrease of 5% in the recall value is compensated by a significant improvement of 15% in precision.

KW - Autonomous Port Surveillance

KW - Multiple Ship Detection

KW - Water Detection

UR - http://www.scopus.com/inward/record.url?scp=84866434911&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-33140-4_39

DO - 10.1007/978-3-642-33140-4_39

M3 - Conference contribution

SN - 9783642331398

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 444

EP - 454

BT - Advanced Concepts for Intelligent Vision Systems - 14th International Conference, ACIVS 2012, Proceedings

T2 - 14th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS 2012)

Y2 - 4 September 2012 through 7 September 2012

ER -

Bao X, Zinger S, Wijnhoven R, De With PHN. Water region detection supporting ship identification in port surveillance. In Advanced Concepts for Intelligent Vision Systems - 14th International Conference, ACIVS 2012, Proceedings. 2012. p. 444-454. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-33140-4_39, 10.1007/978-3-642-33140-4_39

Water region detection supporting ship identification in port surveillance

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this