A novel salient line detection approach based on ant colony optimization algorithm

Xutang Zhang; Yan Liu; Yinling Ma; Hong Liu; Ting Zhuang

doi:10.1007/978-3-319-09333-8_79

A novel salient line detection approach based on ant colony optimization algorithm

Xutang Zhang
, Yan Liu^*
, Yinling Ma
, Hong Liu
, Ting Zhuang

^*Corresponding author for this work

School of Mechatronics Engineering, Harbin Institute of Technology
Harbin Institute of Technology
Harbin Finance University

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

Abstract

In this paper, we propose a novel salient line detection algorithm for 3-dimensional (3D) mesh models based on ant colony optimization algorithm. In proposed method, the heuristic function in ACO transition function is improved based on tensor feature and the relationship between mean curvature information via vertex geometric feature. In addition, the proposed method establishes a similarity measurement criterion of feature points by combining the normal tensor voting with discrete mean curvature. Moreover, a direction control function is utilized to conduct the detection process to a expect direction, which can achieve an interaction between operator and computer. The experimental results show that the proposed method can extract the salient line effectively and precisely.

Original language	English
Title of host publication	Intelligent Computing Theory - 10th International Conference, ICIC 2014, Proceedings
Publisher	Springer Verlag
Pages	721-728
Number of pages	8
ISBN (Print)	9783319093321
DOIs	https://doi.org/10.1007/978-3-319-09333-8_79
State	Published - 2014
Externally published	Yes
Event	10th International Conference on Intelligent Computing, ICIC 2014 - Taiyuan, China Duration: 3 Aug 2014 → 6 Aug 2014

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8588 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Conference on Intelligent Computing, ICIC 2014
Country/Territory	China
City	Taiyuan
Period	3/08/14 → 6/08/14

Keywords

3-dimensional mesh models
ant colony optimization
salient line detection

Access to Document

10.1007/978-3-319-09333-8_79

Cite this

Zhang, X., Liu, Y., Ma, Y., Liu, H., & Zhuang, T. (2014). A novel salient line detection approach based on ant colony optimization algorithm. In Intelligent Computing Theory - 10th International Conference, ICIC 2014, Proceedings (pp. 721-728). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8588 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-09333-8_79

Zhang, Xutang ; Liu, Yan ; Ma, Yinling et al. / A novel salient line detection approach based on ant colony optimization algorithm. Intelligent Computing Theory - 10th International Conference, ICIC 2014, Proceedings. Springer Verlag, 2014. pp. 721-728 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{4eb3129723314fcbae8d39e93cdca98a,

title = "A novel salient line detection approach based on ant colony optimization algorithm",

abstract = "In this paper, we propose a novel salient line detection algorithm for 3-dimensional (3D) mesh models based on ant colony optimization algorithm. In proposed method, the heuristic function in ACO transition function is improved based on tensor feature and the relationship between mean curvature information via vertex geometric feature. In addition, the proposed method establishes a similarity measurement criterion of feature points by combining the normal tensor voting with discrete mean curvature. Moreover, a direction control function is utilized to conduct the detection process to a expect direction, which can achieve an interaction between operator and computer. The experimental results show that the proposed method can extract the salient line effectively and precisely.",

keywords = "3-dimensional mesh models, ant colony optimization, salient line detection",

author = "Xutang Zhang and Yan Liu and Yinling Ma and Hong Liu and Ting Zhuang",

year = "2014",

doi = "10.1007/978-3-319-09333-8\_79",

language = "英语",

isbn = "9783319093321",

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

publisher = "Springer Verlag",

pages = "721--728",

booktitle = "Intelligent Computing Theory - 10th International Conference, ICIC 2014, Proceedings",

address = "德国",

note = "10th International Conference on Intelligent Computing, ICIC 2014 ; Conference date: 03-08-2014 Through 06-08-2014",

}

Zhang, X, Liu, Y, Ma, Y, Liu, H & Zhuang, T 2014, A novel salient line detection approach based on ant colony optimization algorithm. in Intelligent Computing Theory - 10th International Conference, ICIC 2014, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8588 LNCS, Springer Verlag, pp. 721-728, 10th International Conference on Intelligent Computing, ICIC 2014, Taiyuan, China, 3/08/14. https://doi.org/10.1007/978-3-319-09333-8_79

A novel salient line detection approach based on ant colony optimization algorithm. / Zhang, Xutang; Liu, Yan; Ma, Yinling et al.
Intelligent Computing Theory - 10th International Conference, ICIC 2014, Proceedings. Springer Verlag, 2014. p. 721-728 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8588 LNCS).

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

TY - GEN

T1 - A novel salient line detection approach based on ant colony optimization algorithm

AU - Zhang, Xutang

AU - Liu, Yan

AU - Ma, Yinling

AU - Liu, Hong

AU - Zhuang, Ting

PY - 2014

Y1 - 2014

N2 - In this paper, we propose a novel salient line detection algorithm for 3-dimensional (3D) mesh models based on ant colony optimization algorithm. In proposed method, the heuristic function in ACO transition function is improved based on tensor feature and the relationship between mean curvature information via vertex geometric feature. In addition, the proposed method establishes a similarity measurement criterion of feature points by combining the normal tensor voting with discrete mean curvature. Moreover, a direction control function is utilized to conduct the detection process to a expect direction, which can achieve an interaction between operator and computer. The experimental results show that the proposed method can extract the salient line effectively and precisely.

AB - In this paper, we propose a novel salient line detection algorithm for 3-dimensional (3D) mesh models based on ant colony optimization algorithm. In proposed method, the heuristic function in ACO transition function is improved based on tensor feature and the relationship between mean curvature information via vertex geometric feature. In addition, the proposed method establishes a similarity measurement criterion of feature points by combining the normal tensor voting with discrete mean curvature. Moreover, a direction control function is utilized to conduct the detection process to a expect direction, which can achieve an interaction between operator and computer. The experimental results show that the proposed method can extract the salient line effectively and precisely.

KW - 3-dimensional mesh models

KW - ant colony optimization

KW - salient line detection

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DO - 10.1007/978-3-319-09333-8_79

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SN - 9783319093321

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

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BT - Intelligent Computing Theory - 10th International Conference, ICIC 2014, Proceedings

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T2 - 10th International Conference on Intelligent Computing, ICIC 2014

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ER -

Zhang X, Liu Y, Ma Y, Liu H, Zhuang T. A novel salient line detection approach based on ant colony optimization algorithm. In Intelligent Computing Theory - 10th International Conference, ICIC 2014, Proceedings. Springer Verlag. 2014. p. 721-728. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-09333-8_79

A novel salient line detection approach based on ant colony optimization algorithm

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