Skip to main content
SpringerLink
Log in

Integrating salient colors with rotational invariant texture features for image representation in retrieval systems

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Content based image retrieval (CBIR) systems allow searching for visually similar images in large collections based on their contents. Visual contents are usually represented based on their properties like colors, shapes, and textures. In this paper, we propose to integrate two properties of images for constructing a discriminative and robust representation. Firstly, the input image is transformed into the HSV color space and then quantized into a limited number of representative colors. Secondly, texture features based on uniform patterns of rotated local binary patterns (RLBP) are extracted. The characteristics of color histogram populated from the quantized images and texture features are compared and analyzed for image representation. Consequently, the quantized color histogram and histogram of uniform patterns in RLBP are fused together to form a feature vector. Experimental evaluations with frequently used datasets show that the proposed method yields better results as compared to other state-of-the-art techniques.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Ahmad J. et al. (2015) SSH: Salient structures histogram for content based image retrieval. In Network-Based Information Systems (NBiS), 2015 18th international Conference on. IEEE

  2. Ahmad J, Sajjad M, Mehmood I et al (2015) Saliency-weighted graphs for efficient visual content description and their applications in real-time image retrieval systems. J Real-Time Image Proc. https://doi.org/10.1007/s11554-015-0536-0

  3. Ahonen T, Hadid A, Pietikainen M (2006) Face description with local binary patterns: application to face recognition. IEEE Trans Pattern Anal Mach Intell 28(12):2037–2041

    Article  MATH  Google Scholar 

  4. Bala A, Kaur T (2016) Local texton XOR patterns: a new feature descriptor for content-based image retrieval. Eng Sci Technol Int J 19(1):101–112

    Article  Google Scholar 

  5. Boutell M and Luo J (2004) A generalized temporal context model for semantic scene classification. In Computer Vision and Pattern Recognition Workshop, 2004. CVPRW'04. Conference on. IEEE

  6. Eimer M (2014) The neural basis of attentional control in visual search. Trends Cogn Sci 18(10):526–535

    Article  Google Scholar 

  7. Hoi SC et al. (2008) Semi-supervised SVM batch mode active learning for image retrieval. In Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on. IEEE

  8. Duan L-Y, Chen J, Ji R, Huang T, Gao W (2013) Learning compact visual descriptors for low bit rate mobile landmark search. In IJCAI Proceedings-International Joint Conference on Artificial. AI Mag 34(2):67

  9. Junling L et al. (2011) Image retrieval based on weighted blocks and color feature. In Mechatronic Science, Electric Engineering and Computer (MEC), 2011 International Conference on. IEEE

  10. Kastner S, Ungerleider LG (2001) The neural basis of biased competition in human visual cortex. Neuropsychologia 39(12):1263–1276

    Article  Google Scholar 

  11. Liu G-H et al (2010) Image retrieval based on multi-texton histogram. Pattern Recogn 43(7):2380–2389

    Article  MATH  Google Scholar 

  12. Liu G-H et al (2011) Image retrieval based on micro-structure descriptor. Pattern Recogn 44(9):2123–2133

    Article  Google Scholar 

  13. Livingstone MS, Hubel DH (1984) Anatomy and physiology of a color system in the primate visual cortex. J Neurosci 4(1):309–356

    Google Scholar 

  14. Marée R, Geurts P, Wehenkel L (2007) Content-based image retrieval by indexing random subwindows with randomized trees. In Asian Conference on Computer Vision. Springer

  15. Mehta R, Egiazarian K (2016) Dominant rotated local binary patterns (DRLBP) for texture classification. Pattern Recogn Lett 71:16–22

    Article  Google Scholar 

  16. Müller H et al (2001) Performance evaluation in content-based image retrieval: overview and proposals. Pattern Recogn Lett 22(5):593–601

    Article  MATH  Google Scholar 

  17. Murala S, Maheshwari R, Balasubramanian R (2012) Local tetra patterns: a new feature descriptor for content-based image retrieval. IEEE Trans Image Process 21(5):2874–2886

    Article  MathSciNet  MATH  Google Scholar 

  18. Rahimi M, Moghaddam ME (2015) A content-based image retrieval system based on color ton distribution descriptors. SIViP 9(3):691–704

    Article  Google Scholar 

  19. Sethi, I.K., I.L. Coman, and D. Stan. (2001) Mining association rules between low-level image features and high-level concepts. In aerospace/defense sensing, simulation, and controls. International Society for Optics and Photonics

  20. Shao H, Svoboda T, Van Gool L (2003) Zubud-zurich buildings database for image based recognition. Computer Vision Lab, Swiss Federal Institute of Technology, Switzerland, Tech. Rep 260:20

    Google Scholar 

  21. Smeulders AW et al (2000) Content-based image retrieval at the end of the early years. IEEE Trans Pattern Anal Mach Intell 22(12):1349–1380

    Article  Google Scholar 

  22. Takala V, Ahonen T, Pietikäinen M (2005) Block-based methods for image retrieval using local binary patterns. In Scandinavian Conference on Image Analysis. Springer

  23. Tang J, Lewis PH (2007) A study of quality issues for image auto-annotation with the corel dataset. IEEE Trans Circuits Syst Video Technol 17(3):384–389

    Article  Google Scholar 

  24. Vatamanu OA et al. (2013) Content-based image retrieval using local binary pattern, intensity histogram and color coherence vector. In E-health and bioengineering conference (EHB), 2013. IEEE

  25. Walia E, Pal A (2014) Fusion framework for effective color image retrieval. J Vis Commun Image Represent 25(6):1335–1348

    Article  Google Scholar 

  26. Wang X, Wang Z (2013) A novel method for image retrieval based on structure elements’ descriptor. J Vis Commun Image Represent 24(1):63–74

    Article  Google Scholar 

  27. Won CS, Park DK, Park S-J (2002) Efficient use of MPEG-7 edge histogram descriptor. ETRI J 24(1):23–30

    Article  Google Scholar 

  28. Yu Y-H, Lee T-T, Chen P-Y, Kwok N (2014) On-chip real-time feature extraction using semantic annotations for object recognition. J Real-Time Image Proc 9:1–16

  29. Zhao G, Pietikainen M (2007) Dynamic texture recognition using local binary patterns with an application to facial expressions. IEEE Trans Pattern Anal Mach Intell 29(6):915–928

    Article  Google Scholar 

  30. Zhou, J., T. Xu, and W. Gao (2014) Content based image retrieval using local directional pattern and color histogram, In Optimization and Control Techniques and Applications. Springer. p. 197–211

Download references

Acknowledgements

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea Government (MSIP) (No.2016R1A2B4011712).

Author information

Author notes

  1. Muhammad Sajjad and Amin Ullah contributed equally to this work.

Authors and Affiliations

  1. Digital Image Processing Laboratory, Department of Computer Science, Islamia College, Peshawar, Pakistan

    Muhammad Sajjad, Amin Ullah & Naveed Abbas

  2. Intelligent Media Laboratory, College of Software and Convergence Technology, Sejong University, Seoul, Republic of Korea

    Amin Ullah, Jamil Ahmad & Sung Wook Baik

  3. Department of Media Software, Sungkyul University, Anyang, Republic of Korea

    Seungmin Rho

Authors
  1. Muhammad Sajjad
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Amin Ullah
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jamil Ahmad
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Naveed Abbas
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Seungmin Rho
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sung Wook Baik
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sung Wook Baik.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sajjad, M., Ullah, A., Ahmad, J. et al. Integrating salient colors with rotational invariant texture features for image representation in retrieval systems. Multimed Tools Appl 77, 4769–4789 (2018). https://doi.org/10.1007/s11042-017-5010-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-017-5010-5

Keywords

Search

Navigation