Skip to main content
SpringerLink
Log in

Image Search Engine Based on Color Histogram and Zernike Moment

  • Conference paper
  • First Online:
Ubiquitous Networking (UNet 2017)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 10542))

Included in the following conference series:

Abstract

Though numerous approaches were proposed for image recognition, in this paper we proposed implementation of CBIR, using color descriptor combined to the shape features (Zernike moments). A practical and efficient system has been implemented based on image division and extraction color histogram of color from each block, and combined the result vector to the global shape one. We experimented our system on several image bases, and it gave satisfactory results.

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 EPUB and 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

References

  1. Kabbai, L., Abdellaoui, M.: Content based image retrieval using local and global features descriptor. In: 2nd International Conference on Advanced Technologies for Signal and Image Processing - Tunisia ATSIP’2016, 21–24 March 2016 (2016)

    Google Scholar 

  2. Chifa, N., Badri, A., Ruichek, Y.: Powerful combination of color descriptor and LBP descriptor for image retrieval. Int. J. Comput. Appl. Technol. Res. 5(4), 210–214 (2016)

    Google Scholar 

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

    Article  Google Scholar 

  4. Stricker, M.A., Orengo, M.: Similarity of color image. In: Proceedings of Storage and Retrieval for Image and Video Databases, pp. 381–392 (1995)

    Google Scholar 

  5. Hu, M.K.: Visual pattern recognition by moment’s invariants. IRE Trans. Inf. Theory 8, 179–187 (1962)

    MATH  Google Scholar 

  6. Khotanzad, A., Hong, Y.H.: Invariant image recognition by Zernike moments. IEEE Trans. Pattern Anal. Mach. Intell. 12, 489–497 (1990)

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Google Scholar 

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

    Article  Google Scholar 

  11. Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, pp. 886–893. IEEE (2005)

    Google Scholar 

  12. Zeng, S., Huang, R., Wang, H., Kang, Z.: Image retrieval using spatiograms of colors quantized by Gaussian mixture models. Neurocomputiong 171, 673–684 (2016)

    Article  Google Scholar 

  13. Shrivastava, S., Gupta, B., Gupta, M.: Optimization of image retrieval by using HSV color space, Zernike moment & DWT technique. In: 2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), pp. 1–5, Madurai (2015)

    Google Scholar 

  14. Malisiewicz, T., Efros, A.A.: Improving spatial support for objects via multiple segmentations. In: BMVC (2007)

    Google Scholar 

  15. Teague, M.R.: Image analysis via the general theory of moments. J. Opt. Soc. Am. 70(8), 920–930 (1980)

    Article  MathSciNet  Google Scholar 

  16. Amayeh, G., Erol, A., Bebis, G., Nicolescu, M.: Accurate and efficient computation of high order Zernike moments. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds.) ISVC 2005. LNCS, vol. 3804, pp. 462–469. Springer, Heidelberg (2005). doi:10.1007/11595755_56

    Chapter  Google Scholar 

  17. Revaud, J., Lavoué, G., Baskurt, A.: Une nouvelle mesure de distance entre descripteurs de moments de Zernike pour une similarité optimale et un angle de rotation entre les images. In: CORESA, March 2009

    Google Scholar 

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

    Article  Google Scholar 

  19. Chifa, N., Badri, A., Ruichek, Y., Sahel, A., Safi, K.: 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. SCI, vol. 672, pp. 69–80. Springer, Cham (2017). doi:10.1007/978-3-319-46245-5_5

    Chapter  Google Scholar 

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

    Article  Google Scholar 

  21. ElAlami, M.E.: 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. EEA&TI Laboratory, Faculty of Sciences and Techniques (FSTM) Mohammedia, Hassan II University of Casablanca, Casablanca, Morocco

    Nawal Chifa, Abdelmajid Badri & Aicha Sahel

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

    Yassine Ruichek

Authors
  1. Nawal Chifa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Abdelmajid Badri
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yassine Ruichek
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Aicha Sahel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nawal Chifa .

Editor information

Editors and Affiliations

  1. ENSEM, Hassan II University of Casablanca, Casablanca, Morocco

    Essaid Sabir

  2. Universidad Carlos III de Madrid, Madrid, Spain

    Ana García Armada

  3. International University of Rabat, Morocco, and University of Leeds, UK, Leeds, United Kingdom

    Mounir Ghogho

  4. CentraleSupélec LANEAS, Gif-sur-Yvette, France

    Mérouane Debbah

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Chifa, N., Badri, A., Ruichek, Y., Sahel, A. (2017). Image Search Engine Based on Color Histogram and Zernike Moment. In: Sabir, E., García Armada, A., Ghogho, M., Debbah, M. (eds) Ubiquitous Networking. UNet 2017. Lecture Notes in Computer Science(), vol 10542. Springer, Cham. https://doi.org/10.1007/978-3-319-68179-5_55

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-68179-5_55

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68178-8

  • Online ISBN: 978-3-319-68179-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation