Skip to main content
SpringerLink
Log in

Combined Retrieval Strategies for Images with and without Distinct Objects

  • Conference paper
Advanced Concepts for Intelligent Vision Systems (ACIVS 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6474))

Abstract

This paper presents the design of an all-season image retrieval system. The system handles the images with and without distinct object(s) using different retrieval strategies. Firstly, based on the visual contrasts and spatial information of an image, a neural network is trained to pre-classify an image as distinct-object or no-distinct-object category by using the Back Propagation Through Structure (BPTS) algorithm. In the second step, an image with distinct object(s) is processed by an attention-driven retrieval strategy emphasizing distinct objects. On the other hand, an image without distinct object(s) (e.g., a scenery images) is processed by a fusing-all retrieval strategy. An improved performance can be obtained by using this combined approach.

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

Access this chapter

Log in via an institution
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.

References

  1. Fu, H., Chi, Z., Feng, D.: Attention-Driven Image Interpretation with Application to Image Retrieval. Pattern Recognition 39(9), 1604–1621 (2006)

    Article  MATH  Google Scholar 

  2. Fu, H., Chi, Z., Feng, D.: An Efficient Algorithm for Attention-Driven Image Interpretation from Segments. Pattern Recognition 42(1), 126–140 (2009)

    Article  MATH  Google Scholar 

  3. Vu, K., Hua, K.A., Tavanapong, W.: Image Retrieval Based on Regions of Interest. IEEE Transactions on Knowledge and Data Engineering 15(4), 1045–1049 (2003)

    Article  Google Scholar 

  4. Tian, Q., Wu, Y., Huang, T.S.: Combine User Defined Region-Of-Interest and Spatial Layout for Image Retrieval. In: IEEE International Conference on Image Processing, vol. 3, pp. 746–749 (2000)

    Google Scholar 

  5. Zhang, J., Yoo, C.W., Ha, S.W.: ROI Based Natural Image Retrieval Using Color and Texture Feature. In: Proceedings - Fourth International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2007, vol. 4, art. no. 4406479, pp. 740–744 (2007)

    Google Scholar 

  6. Zhang, Q., Izquierdo, E.: Adaptive Salient Block-Based Image Retrieval in Multi-Feature Space. Signal Processing: Image Communication 22(6), 591–603 (2007)

    Google Scholar 

  7. Hare, J.S., Lewis, P.H.: Salient Regions for Query by Image Content. In: Enser, P.G.B., Kompatsiaris, Y., O’Connor, N.E., Smeaton, A., Smeulders, A.W.M. (eds.) CIVR 2004. LNCS, vol. 3115, pp. 317–325. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  8. Guan, J., Qiu, G.: Modeling User Feedback Using a Hierarchical Graphical Model for Interactive Image Retrieval. In: Ip, H.H.-S., Au, O.C., Leung, H., Sun, M.-T., Ma, W.-Y., Hu, S.-M. (eds.) PCM 2007. LNCS (LNAI), vol. 4810, pp. 18–29. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  9. Golloer, G., Kuchler, A.: Learning Task-Dependent Distributed Representations by Backpropagation through Structure. In: IEEE International Conferences on Neural Networks, pp. 347–352 (1996)

    Google Scholar 

  10. Cho, S.Y., Chi, Z.: Genetic Evolution Processing of Data Structures for Image Classification. IEEE Transactions on Knowledge and Data Engineering 17(2), 216–231 (2005)

    Article  Google Scholar 

  11. Cho, S.Y., Chi, Z., Wang, Z., Siu, W.C.: An efficient learning algorithm for adaptive processing of data structure. Neural Processing letter 17(2), 175–190 (2003)

    Article  MATH  Google Scholar 

  12. Fu, H., Chi, Z., Feng, D., Zou, W., Lo, K., Zhao, X.: Pre-classification module for an all-season image retrieval system. In: Proceedings of International Joint Conference on Neural Networks, Orlando, Florida, USA, paper 1688, 5 pages (August 12-17, 2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong

    Hong Fu, Zheru Chi & Dagan Feng

  2. Department of Computer Science, Chu Hai College of Higher Education, Hong Kong

    Hong Fu

  3. School of Information Technologies, The University of Sydney, NSW, 2006, Australia

    Dagan Feng

Authors
  1. Hong Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zheru Chi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dagan Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. DGA/D4S/MRIS, CEP/GIP, 16 bis avenue Prieur de la côte d’or, 94114, Arcueil, France

    Jacques Blanc-Talon

  2. Canon Information Systems Research Australia, Sydney, Australia

    Don Bone

  3. Telecommunications and Information processing (TELIN), Ghent University, St.-Pietersnieuwstraat 41, B9000, Ghent, Belgium

    Wilfried Philips

  4. CSIRO ICT Centre, ICT Centre, Po Box 76, NSW 1710, Epping, Sydney, Australia

    Dan Popescu

  5. Physics, University of Antwerp, Universiteitsplein 1; Building N. 2610, Wilrijk, Belgium

    Paul Scheunders

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Fu, H., Chi, Z., Feng, D. (2010). Combined Retrieval Strategies for Images with and without Distinct Objects. In: Blanc-Talon, J., Bone, D., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2010. Lecture Notes in Computer Science, vol 6474. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17688-3_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-17688-3_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17687-6

  • Online ISBN: 978-3-642-17688-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation