Color-based oil spill image segmentation

A. B. Osman; Mark Ovinis; Mahadi A. Ismael; M. H. Fakhruldin; I. Faye

doi:10.1063/1.5075603

Color-based oil spill image segmentation

A. B. Osman^*, Mark Ovinis, Mahadi A. Ismael, M. H. Fakhruldin, I. Faye

^*Corresponding author for this work

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

Abstract

Oil spill image segmentation is an important task for quantifying the total amount of spilled oil. However, segmentation of oil region from images is a challenging problem. This is due to un-defined edge between oil and sea water. This paper proposes a novel approach based on oil color. The proposed color-based method segments the oil spill region based on clustering the colors of oil and water within the image into various groups, from which the oiled region can be segmented and defined. A k-mean cluster was applied to differentiate between the various colors. As a result, the color-based method able to determine the oiled region. A comparison to classical Otsu thresholding method showed that the color-based method had a better oil segmentation.

Original language	English
Title of host publication	6th International Conference on Production, Energy and Reliability 2018
Subtitle of host publication	World Engineering Science and Technology Congress, ESTCON 2018
Editors	Mohammad Shakir Nasif, Shaharin Anwar B. Sulaiman, Srinivasa Rao Pedapati, Hamdan Ya, Othman B. Mamat, William Pao King Soon
Publisher	American Institute of Physics Inc.
ISBN (Electronic)	9780735417618
DOIs	https://doi.org/10.1063/1.5075603
State	Published - 13 Nov 2018
Externally published	Yes
Event	6th International Conference on Production, Energy and Reliability, ICPER 2018 - Kuala Lumpur, Malaysia Duration: 13 Aug 2018 → 14 Aug 2018

Publication series

Name	AIP Conference Proceedings
Volume	2035
ISSN (Print)	0094-243X
ISSN (Electronic)	1551-7616

Conference

Conference	6th International Conference on Production, Energy and Reliability, ICPER 2018
Country/Territory	Malaysia
City	Kuala Lumpur
Period	13/08/18 → 14/08/18

Bibliographical note

Publisher Copyright:
© 2018 Author(s).

Keywords

K-mean
oil color
remote sensing

ASJC Scopus subject areas

General Physics and Astronomy

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1063/1.5075603

Cite this

Osman, A. B., Ovinis, M., Ismael, M. A., Fakhruldin, M. H., & Faye, I. (2018). Color-based oil spill image segmentation. In M. S. Nasif, S. A. B. Sulaiman, S. R. Pedapati, H. Ya, O. B. Mamat, & W. P. K. Soon (Eds.), 6th International Conference on Production, Energy and Reliability 2018: World Engineering Science and Technology Congress, ESTCON 2018 Article 080004 (AIP Conference Proceedings; Vol. 2035). American Institute of Physics Inc.. https://doi.org/10.1063/1.5075603

Osman, A. B. ; Ovinis, Mark ; Ismael, Mahadi A. et al. / Color-based oil spill image segmentation. 6th International Conference on Production, Energy and Reliability 2018: World Engineering Science and Technology Congress, ESTCON 2018. editor / Mohammad Shakir Nasif ; Shaharin Anwar B. Sulaiman ; Srinivasa Rao Pedapati ; Hamdan Ya ; Othman B. Mamat ; William Pao King Soon. American Institute of Physics Inc., 2018. (AIP Conference Proceedings).

@inproceedings{fd69bd9c069b4f38b8596f77f80b1a5c,

title = "Color-based oil spill image segmentation",

abstract = "Oil spill image segmentation is an important task for quantifying the total amount of spilled oil. However, segmentation of oil region from images is a challenging problem. This is due to un-defined edge between oil and sea water. This paper proposes a novel approach based on oil color. The proposed color-based method segments the oil spill region based on clustering the colors of oil and water within the image into various groups, from which the oiled region can be segmented and defined. A k-mean cluster was applied to differentiate between the various colors. As a result, the color-based method able to determine the oiled region. A comparison to classical Otsu thresholding method showed that the color-based method had a better oil segmentation.",

keywords = "K-mean, oil color, remote sensing",

author = "Osman, \{A. B.\} and Mark Ovinis and Ismael, \{Mahadi A.\} and Fakhruldin, \{M. H.\} and I. Faye",

note = "Publisher Copyright: {\textcopyright} 2018 Author(s).; 6th International Conference on Production, Energy and Reliability, ICPER 2018 ; Conference date: 13-08-2018 Through 14-08-2018",

year = "2018",

month = nov,

day = "13",

doi = "10.1063/1.5075603",

language = "English",

series = "AIP Conference Proceedings",

publisher = "American Institute of Physics Inc.",

editor = "Nasif, \{Mohammad Shakir\} and Sulaiman, \{Shaharin Anwar B.\} and Pedapati, \{Srinivasa Rao\} and Hamdan Ya and Mamat, \{Othman B.\} and Soon, \{William Pao King\}",

booktitle = "6th International Conference on Production, Energy and Reliability 2018",

}

Osman, AB, Ovinis, M, Ismael, MA, Fakhruldin, MH & Faye, I 2018, Color-based oil spill image segmentation. in MS Nasif, SAB Sulaiman, SR Pedapati, H Ya, OB Mamat & WPK Soon (eds), 6th International Conference on Production, Energy and Reliability 2018: World Engineering Science and Technology Congress, ESTCON 2018., 080004, AIP Conference Proceedings, vol. 2035, American Institute of Physics Inc., 6th International Conference on Production, Energy and Reliability, ICPER 2018, Kuala Lumpur, Malaysia, 13/08/18. https://doi.org/10.1063/1.5075603

Color-based oil spill image segmentation. / Osman, A. B.; Ovinis, Mark; Ismael, Mahadi A. et al.
6th International Conference on Production, Energy and Reliability 2018: World Engineering Science and Technology Congress, ESTCON 2018. ed. / Mohammad Shakir Nasif; Shaharin Anwar B. Sulaiman; Srinivasa Rao Pedapati; Hamdan Ya; Othman B. Mamat; William Pao King Soon. American Institute of Physics Inc., 2018. 080004 (AIP Conference Proceedings; Vol. 2035).

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

TY - GEN

T1 - Color-based oil spill image segmentation

AU - Osman, A. B.

AU - Ovinis, Mark

AU - Ismael, Mahadi A.

AU - Fakhruldin, M. H.

AU - Faye, I.

PY - 2018/11/13

Y1 - 2018/11/13

N2 - Oil spill image segmentation is an important task for quantifying the total amount of spilled oil. However, segmentation of oil region from images is a challenging problem. This is due to un-defined edge between oil and sea water. This paper proposes a novel approach based on oil color. The proposed color-based method segments the oil spill region based on clustering the colors of oil and water within the image into various groups, from which the oiled region can be segmented and defined. A k-mean cluster was applied to differentiate between the various colors. As a result, the color-based method able to determine the oiled region. A comparison to classical Otsu thresholding method showed that the color-based method had a better oil segmentation.

AB - Oil spill image segmentation is an important task for quantifying the total amount of spilled oil. However, segmentation of oil region from images is a challenging problem. This is due to un-defined edge between oil and sea water. This paper proposes a novel approach based on oil color. The proposed color-based method segments the oil spill region based on clustering the colors of oil and water within the image into various groups, from which the oiled region can be segmented and defined. A k-mean cluster was applied to differentiate between the various colors. As a result, the color-based method able to determine the oiled region. A comparison to classical Otsu thresholding method showed that the color-based method had a better oil segmentation.

KW - K-mean

KW - oil color

KW - remote sensing

UR - https://www.scopus.com/pages/publications/85057345191

U2 - 10.1063/1.5075603

DO - 10.1063/1.5075603

M3 - Conference contribution

AN - SCOPUS:85057345191

T3 - AIP Conference Proceedings

BT - 6th International Conference on Production, Energy and Reliability 2018

A2 - Nasif, Mohammad Shakir

A2 - Sulaiman, Shaharin Anwar B.

A2 - Pedapati, Srinivasa Rao

A2 - Ya, Hamdan

A2 - Mamat, Othman B.

A2 - Soon, William Pao King

PB - American Institute of Physics Inc.

T2 - 6th International Conference on Production, Energy and Reliability, ICPER 2018

Y2 - 13 August 2018 through 14 August 2018

ER -

Osman AB, Ovinis M, Ismael MA, Fakhruldin MH, Faye I. Color-based oil spill image segmentation. In Nasif MS, Sulaiman SAB, Pedapati SR, Ya H, Mamat OB, Soon WPK, editors, 6th International Conference on Production, Energy and Reliability 2018: World Engineering Science and Technology Congress, ESTCON 2018. American Institute of Physics Inc. 2018. 080004. (AIP Conference Proceedings). doi: 10.1063/1.5075603

Color-based oil spill image segmentation

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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Cite this