Image segmentation using adaptively selected color space

Gu Fang; N. M. Kwok

doi:10.1109/ROBIO.2009.5420555

Image segmentation using adaptively selected color space

Gu Fang, N. M. Kwok

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

4 Citations (Scopus)

Abstract

Image segmentation is an important and difficult task in computer vision applications. Various methods have been introduced in the past to use gray-level histogram in deciding the segmentation threshold for monochrome images. With the reducing price of color cameras, different color spaces have also been considered in color image based segmentations. In this paper, a study of the effect of color spaces is presented and a segmentation strategy is introduced to select the most effective space in which the segmentation result could be improved. Experimental results show that the proposed method can provide robust segmentation outcomes subject to parts with different colors and under different illumination conditions.

Original language	English
Title of host publication	Proceedings of the 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO 2009): Guilin, China, 19-23 December 2009
Publisher	IEEE
Pages	1838-1843
Number of pages	6
ISBN (Print)	9781424447756
DOIs	https://doi.org/10.1109/ROBIO.2009.5420555
Publication status	Published - 2009
Event	IEEE International Conference on Robotics and Biomimetics - Duration: 7 Dec 2011 → …

Conference

Conference	IEEE International Conference on Robotics and Biomimetics
Period	7/12/11 → …

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10.1109/ROBIO.2009.5420555

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title = "Image segmentation using adaptively selected color space",

abstract = "Image segmentation is an important and difficult task in computer vision applications. Various methods have been introduced in the past to use gray-level histogram in deciding the segmentation threshold for monochrome images. With the reducing price of color cameras, different color spaces have also been considered in color image based segmentations. In this paper, a study of the effect of color spaces is presented and a segmentation strategy is introduced to select the most effective space in which the segmentation result could be improved. Experimental results show that the proposed method can provide robust segmentation outcomes subject to parts with different colors and under different illumination conditions.",

author = "Gu Fang and Kwok, {N. M.}",

year = "2009",

doi = "10.1109/ROBIO.2009.5420555",

language = "English",

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booktitle = "Proceedings of the 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO 2009): Guilin, China, 19-23 December 2009",

publisher = "IEEE",

note = "IEEE International Conference on Robotics and Biomimetics ; Conference date: 07-12-2011",

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AU - Fang, Gu

AU - Kwok, N. M.

PY - 2009

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N2 - Image segmentation is an important and difficult task in computer vision applications. Various methods have been introduced in the past to use gray-level histogram in deciding the segmentation threshold for monochrome images. With the reducing price of color cameras, different color spaces have also been considered in color image based segmentations. In this paper, a study of the effect of color spaces is presented and a segmentation strategy is introduced to select the most effective space in which the segmentation result could be improved. Experimental results show that the proposed method can provide robust segmentation outcomes subject to parts with different colors and under different illumination conditions.

AB - Image segmentation is an important and difficult task in computer vision applications. Various methods have been introduced in the past to use gray-level histogram in deciding the segmentation threshold for monochrome images. With the reducing price of color cameras, different color spaces have also been considered in color image based segmentations. In this paper, a study of the effect of color spaces is presented and a segmentation strategy is introduced to select the most effective space in which the segmentation result could be improved. Experimental results show that the proposed method can provide robust segmentation outcomes subject to parts with different colors and under different illumination conditions.

UR - http://handle.uws.edu.au:8081/1959.7/562590

UR - http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5413559

U2 - 10.1109/ROBIO.2009.5420555

DO - 10.1109/ROBIO.2009.5420555

M3 - Conference Paper

SN - 9781424447756

SP - 1838

EP - 1843

BT - Proceedings of the 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO 2009): Guilin, China, 19-23 December 2009

PB - IEEE

T2 - IEEE International Conference on Robotics and Biomimetics

Y2 - 7 December 2011

ER -

Image segmentation using adaptively selected color space

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