Skip to main content

Layered Cooperation of Macro Agents and Micro Agents in Cooperative Active Contour Model

  • Conference paper
Agent Computing and Multi-Agent Systems (PRIMA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5044))

Included in the following conference series:

  • 718 Accesses

Abstract

We have proposed Multi-Snake, which realizes boundary detection in image recognition with the layered cooperation of micro agents and macro agents. Cooperation in a set of micro agents constructs the behavior of a macro agent, and cooperation of the micro agents are integrated to cooperation of the macro agents. This mechanism makes the application more dynamic and flexible. Our previous proposals dealt with cooperation between some macro agents of the same kind. This paper focuses on the cooperation of macro agents of different kinds: sensor-based macro agents and model-based macro agents. We show that our proposal makes estimation improved and more robust. We verify the effectiveness of our proposal through some experiments using artificial images and real images.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active contour model. Int.J. Computer Vision 1(4), 321–331 (1988)

    Article  Google Scholar 

  2. Matsumoto, N., Yoshida, N., Narazaki, S.: Active Contour Model with Decentralized Cooperative Processing. IIEEJ 34(6), 747–752 (2005)

    Google Scholar 

  3. Matsumoto, N., Yoshida, N., Narazaki, S.: Cooperative Active Contour Model and Its Application to Remote Sensing. In: Proc. ACM 21st Annual Symp. on Applied Computing, pp. 44–45 (2006)

    Google Scholar 

  4. Matsumoto, N., Yoshida, N., Narazaki, S.: Improvement of Active Contour Model with Decentralized Cooperative Processing and Its Application to Remote Sensing. International Journal of Knowledge-Based and Intelligent Engineering Systems 11(3), 169–179 (2007)

    Article  Google Scholar 

  5. Matsumoto, N., Yoshida, N., Narazaki, S.: Curvature Multi-Snake: Cooperative Snakes with Curvature-Based Simple Modeling. In: Proceedings of International Workshop on Advanced Image Technology 2007, pp. 632–637 (2007)

    Google Scholar 

  6. Etoh, M., Shirai, Y., Asada, M.: Active Contour Extraction Based on Region Descriptions Obtained from Clustering. IEICE Transactions(D-II) J75-D-II(7), 1111–1119 (1992)

    Google Scholar 

  7. Zhu, S., Yuille, A.: Region competition: Unifying snakes, region growing, and bayes/MDL for multiband image segmentation. IEEE Trans., PAMI 18(9), 884–900 (1996)

    Article  Google Scholar 

  8. Wada, T., Nomura, Y., Matsuyama, T.: Cooperative Distributed Image Segmentation. IPSJ Journal 36(4), 879–891 (1995) (in Japanese)

    Google Scholar 

  9. Matsuzawa, Y., Abe, T.: Region Extraction Using Competition of Multiple Active Contour Models. IEICE Transactions(D-II) J83-D-II(4), 1100–1109 (2000) (in Japanese)

    Google Scholar 

  10. Staib, L., Duncan, J.: Boundary finding with parametrically deformable models. IEEE Trans. PAMI 14(11), 1061–1075 (1992)

    Article  Google Scholar 

  11. Umeyama, S.: Contour extraction using a complex autoregressive model. Systems and Computers in Japan 28(1), 66–73 (1997)

    Article  Google Scholar 

  12. Cootes, T., Taylor, C., Cooper, D., Graham, J.: Active Shape models – Their Training and Application. Computer Vision and Image Understanding 61(1), 38–59 (1995)

    Article  Google Scholar 

  13. Lai, K., Chin, R.: Deformable contours: Modeling and extraction. IEEE Trans. PAMI 17(11), 1084–1090 (1995)

    Article  Google Scholar 

  14. Wang, Y., Staib, L.: Boundary finding with prior shape and smoothness models. IEEE Trans. PAMI 22(7), 738–743 (2000)

    Article  Google Scholar 

  15. Olstad, B., Torp, A.: Encoding of a priori information in active contour models. IEEE Trans. PAMI 18(9), 863–872 (1996)

    Article  Google Scholar 

  16. Matsuzawa, Y., Abe, T., Kumazawa, I.: Active Contour Model Using Shape Information Obtaned from Initial Contour. IEICE Transactions(D-II) J85-D-II(9), 1436–1445 (2002)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Matsumoto, N., Yoshida, N., Narazaki, S. (2009). Layered Cooperation of Macro Agents and Micro Agents in Cooperative Active Contour Model. In: Ghose, A., Governatori, G., Sadananda, R. (eds) Agent Computing and Multi-Agent Systems. PRIMA 2007. Lecture Notes in Computer Science(), vol 5044. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01639-4_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-01639-4_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01638-7

  • Online ISBN: 978-3-642-01639-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics