Skip to main content
SpringerLink
Log in

Efficient Combination of Color, Texture and Shape Descriptor, Using SLIC Segmentation for Image Retrieval

  • Chapter
  • First Online:
Artificial Intelligence and Computer Vision

Part of the book series: Studies in Computational Intelligence ((SCI,volume 672 ))

Abstract

In this article we present a novel method of extraction and combination descriptor to represent image. First we extract a descriptor shape (HOG) from entire image, and in second we applied method of segmentation and then we extract the color and texture descriptor from each segment in order to have a local and global aspect for each image. These characteristics will be concatenate, stored and compared to those of the image query using the Euclidean distance. The performance of this system is evaluated with a precision factor. The results experimental show a good performance.

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 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover 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

References

  1. X. Hu, G. Wang, H. Wu, H. Lu, Rotation-invariant texture retrieval based on complementary features, in Proceedings of International Symposium on Computer, Consumer and Control, 2014, pp. 311–314

    Google Scholar 

  2. M.J. Swain, D.H. Ballard, Color indexing. Int. J. Comput. Vision 7(1), 11–32 (1991)

    Article  Google Scholar 

  3. M.A. Stricker, M. Orengo, Similarity of color image, in Proceedings of Storage an Retrieval for Image and Video Databases, 1995, pp. 381–392

    Google Scholar 

  4. D.K. Park, Y.S. Jeon, C.S. Won, Efficient use of local edge histogram descriptor, in Proceedings of ACM Workshops on Multimedia, 2000, pp. 51–54

    Google Scholar 

  5. T. Ojala, M. Pietikainen, D. Harwood, A comparative study of texture measures with classification based on feature distribution. Pattern Recogn. 29, 51–59 (1996)

    Article  Google Scholar 

  6. D.G. Lowe, Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60(2), 91–110 (2004)

    Article  Google Scholar 

  7. Y. Ke, R. Sukthankar, PCA-SIFT: a more distinctive representation for local image descriptors, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, 2004, pp. 506–513

    Google Scholar 

  8. H. Bay, A. Ess, T. Tuytelaars, L.V. Gool, SURF: speeded up robust features. Comput. Vis. Image Underst. 110(3), 346–359 (2008)

    Article  Google Scholar 

  9. L. Feng, J. Wu, S. Liu, H. Zhang, Global correlation descriptor: a novel image representation for image retrieval. Representation, 2015, pp. 104–114

    Google Scholar 

  10. N. Dalal, B. Triggs, Histograms of oriented gradients for human detection, in IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2005. IEEE, 2005, vol. 1, pp. 886–893

    Google Scholar 

  11. T. Malisiewicz, A.A. Efros, Improving spatial support for objects via multiple segmentations, 2007—repository.cmu.edu

    Google Scholar 

  12. X. Ren, J. Malik, Learning a classification model for segmentation, in ICCV ‘03, vol. 1, pp. 10–17, Nice 2003

    Google Scholar 

  13. G. Mori, X. Ren, A. Efros, J. Malik, Recovering human body configurations: combining segmentation and recognition, in CVPR ‘04, vol. 2, pp. 326–333, Washington, DC 2004

    Google Scholar 

  14. R. Achanta, A. Shaji, K. Smith, A. Lucchi, P.Fua, S. Susstrunk, SLIC Super-pixels; EPFL Technical Report 149300, 2010

    Google Scholar 

  15. H.Y. Lee, H.K. Lee, Y.H. Ha, Spatial color descriptor for image retrieval and video segmentation. IEEE Trans. Multim. 5(3) (2003)

    Google Scholar 

  16. B.S. Manjunath, J.-R. Ohm, V.V. Vasudevan, A. Yamada, Color and texture descriptors. IEEE Trans. Circuits Syst. Video Technol. 11(6) (2001)

    Google Scholar 

  17. J. Yu, Z. Qin, T. Wan, X. Zhang, Feature integration analysis of bag-of-features model for image retrieval. Neurocomputing 120, 355–364 (2013)

    Google Scholar 

  18. M. Subrahmanyam, Q.M.J. Wu, R.P. Maheshwari, R. Balasubramanian, Modified color motif co-occurrence matrix for image indexing and retrieval. Comput. Electr. Eng. 39, 762–774 (2013)

    Article  Google Scholar 

  19. A. Irtaza, M.A. Jaffar, E. Aleisa, T.S. Choi, Embedding neural networks for semantic association in content based image retrieval. Multim. Tool Appl. 72(2), 1911–1931 (2014)

    Article  Google Scholar 

  20. M.E. ElAlami, A new matching strategy for content based image retrieval system. Appl. Soft Comput. 14, 407–418 (2014)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Sciences and Techniques (FSTM), EEA&TI Laboratory, Hassan II University of Casablanca, Mohammedia, Morocco

    N. Chifa, A. Badri, A. Sahel & K. Safi

  2. IRIES-SET-UTBM, 90010, Belfort Cedex, France

    Y. Ruichek

Authors
  1. N. Chifa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Badri
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Y. Ruichek
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. A. Sahel
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. K. Safi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to N. Chifa .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering and Electronics, Kyushu Institute of Technology, Fukuoka, Japan

    Huimin Lu

  2. School of Information Engineering, Yangzhou University, Yangzhou, China

    Yujie Li

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Chifa, N., Badri, A., Ruichek, Y., Sahel, A., Safi, K. (2017). Efficient Combination of Color, Texture and Shape Descriptor, Using SLIC Segmentation for Image Retrieval. In: Lu, H., Li, Y. (eds) Artificial Intelligence and Computer Vision. Studies in Computational Intelligence, vol 672 . Springer, Cham. https://doi.org/10.1007/978-3-319-46245-5_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-46245-5_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46244-8

  • Online ISBN: 978-3-319-46245-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation