The study of the auto color image segmentation

Jian Zhuang; Haifeng Du; Jinhua Zhang; Sun'an Wang

doi:10.1007/11596981_136

The study of the auto color image segmentation

Jian Zhuang
, Haifeng Du
, Jinhua Zhang
, Sun'an Wang

School of Public Policy and Administration

Xi'an Jiaotong University

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

3 Scopus citations

Abstract

Auto image segmentation can segment the image without operators interfering and is an important technique in the image processing. The Boltzmann-Color- Image-Segmentation (BCIS), which could control the degree of segmentation by adjusting the temperature parameter, is designed based on the Boltzmann-theory and the Metropolis-rule in the paper. Then the criterion function of image segmentation, which could balance between the number of segmented region and the affinity of the segmented image with the original image, is presented. Based the BCIS and Criterion function, the auto color image segmentation is schemed out by using the artificial immune algorithm. Experiments showed that the color image segmentation algorithm, which we designed in the paper, had the good capabilities.

Original language	English
Title of host publication	Computational Intelligence and Security - International Conference, CIS 2005, Proceedings
Pages	923-928
Number of pages	6
DOIs	https://doi.org/10.1007/11596981_136
State	Published - 2005
Event	International Conference on Computational Intelligence and Security, CIS 2005 - Xi'an, China Duration: 15 Dec 2005 → 19 Dec 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3802 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Computational Intelligence and Security, CIS 2005
Country/Territory	China
City	Xi'an
Period	15/12/05 → 19/12/05

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10.1007/11596981_136

Cite this

Zhuang, J., Du, H., Zhang, J., & Wang, S. (2005). The study of the auto color image segmentation. In Computational Intelligence and Security - International Conference, CIS 2005, Proceedings (pp. 923-928). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3802 LNAI). https://doi.org/10.1007/11596981_136

@inproceedings{fd5f3b2a2a964b47ba824e9e959e1640,

title = "The study of the auto color image segmentation",

abstract = "Auto image segmentation can segment the image without operators interfering and is an important technique in the image processing. The Boltzmann-Color- Image-Segmentation (BCIS), which could control the degree of segmentation by adjusting the temperature parameter, is designed based on the Boltzmann-theory and the Metropolis-rule in the paper. Then the criterion function of image segmentation, which could balance between the number of segmented region and the affinity of the segmented image with the original image, is presented. Based the BCIS and Criterion function, the auto color image segmentation is schemed out by using the artificial immune algorithm. Experiments showed that the color image segmentation algorithm, which we designed in the paper, had the good capabilities.",

author = "Jian Zhuang and Haifeng Du and Jinhua Zhang and Sun'an Wang",

year = "2005",

doi = "10.1007/11596981\_136",

language = "英语",

isbn = "3540308199",

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

pages = "923--928",

booktitle = "Computational Intelligence and Security - International Conference, CIS 2005, Proceedings",

note = "International Conference on Computational Intelligence and Security, CIS 2005 ; Conference date: 15-12-2005 Through 19-12-2005",

}

Zhuang, J, Du, H, Zhang, J & Wang, S 2005, The study of the auto color image segmentation. in Computational Intelligence and Security - International Conference, CIS 2005, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3802 LNAI, pp. 923-928, International Conference on Computational Intelligence and Security, CIS 2005, Xi'an, China, 15/12/05. https://doi.org/10.1007/11596981_136

The study of the auto color image segmentation. / Zhuang, Jian; Du, Haifeng; Zhang, Jinhua et al.
Computational Intelligence and Security - International Conference, CIS 2005, Proceedings. 2005. p. 923-928 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3802 LNAI).

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

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N2 - Auto image segmentation can segment the image without operators interfering and is an important technique in the image processing. The Boltzmann-Color- Image-Segmentation (BCIS), which could control the degree of segmentation by adjusting the temperature parameter, is designed based on the Boltzmann-theory and the Metropolis-rule in the paper. Then the criterion function of image segmentation, which could balance between the number of segmented region and the affinity of the segmented image with the original image, is presented. Based the BCIS and Criterion function, the auto color image segmentation is schemed out by using the artificial immune algorithm. Experiments showed that the color image segmentation algorithm, which we designed in the paper, had the good capabilities.

AB - Auto image segmentation can segment the image without operators interfering and is an important technique in the image processing. The Boltzmann-Color- Image-Segmentation (BCIS), which could control the degree of segmentation by adjusting the temperature parameter, is designed based on the Boltzmann-theory and the Metropolis-rule in the paper. Then the criterion function of image segmentation, which could balance between the number of segmented region and the affinity of the segmented image with the original image, is presented. Based the BCIS and Criterion function, the auto color image segmentation is schemed out by using the artificial immune algorithm. Experiments showed that the color image segmentation algorithm, which we designed in the paper, had the good capabilities.

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DO - 10.1007/11596981_136

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Y2 - 15 December 2005 through 19 December 2005

ER -

The study of the auto color image segmentation

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