Skip to main content
SpringerLink
Log in

Analysis and Optimization of Feature Extraction Techniques for Content Based Image Retrieval

  • Conference paper
  • First Online:
Information Systems Design and Intelligent Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 435))

  • 1545 Accesses

Abstract

The requirement of improved image processing methods to index increasing image database that results in an alarming need of content based image retrieval systems, which are search engines for images and also is an indexing technique for large collection of image databases. In this paper, an approach to improve the accuracy of content based image retrieval is proposed that uses the genetic algorithm, a novel and powerful global exploration approach. The classification techniques—Neural Network and Nearest Neighbor have been compared in the absence and presence of Genetic Algorithm. The computational results obtained shows the significant increase in the accuracy by incorporating genetic algorithm for both the classification techniques implemented.

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 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
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

Similar content being viewed by others

References

  1. Ezekiel, S., Alford, M.G., Ferris, D., Jones, E., Bubalo, A., Gorniak, M., Blasch, E.: Multi-Scale Decomposition Tool for Content Based Image Retrieval. In: Applied Imagery Pattern Recognition Workshop (AIPR): Sensing of Control and Augmentation, IEEE, pp. 1–5. (2013).

    Google Scholar 

  2. Agarwal, M.: Integrated Features of Haar-like Wavelet Filters. In: 7th International Conference on Contemporary Computing (IC3), IEEE, pp. 370–375. (2014).

    Google Scholar 

  3. Jeyabharathi, D., Suruliandi, A.: Performance Analysis of Feature Extraction and Classification Techniques in CBIR. In: International Conference on Circuits, Power and Computing Technologies (ICCPCT), IEEE, pp. 1211–1214. (2013).

    Google Scholar 

  4. Syam, B., Victor, J.S.R., Rao, Y.S.: Efficient Similarity Measure via Genetic Algorithm for Content Based Medical Image Retrieval with Extensive Features. In: International Multi-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4 s), IEEE, pp. 704–711. (2013).

    Google Scholar 

  5. Ligade, A.N., Patil, M.R.: Optimized Content Based Image Retrieval Using Genetic Algorithm with Relevance Feedback Technique. In: International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR), pp. 49–54, TJPRC, (2013).

    Google Scholar 

  6. Rashedi, E., Nezamabadi-pour, H.: Improving the Precision of CBIR Systems by Feature Selection Using Binary Gravitational Search Algorithm. In: 16th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP), IEEE, pp. 039–042, (2012).

    Google Scholar 

  7. Pighetti, R., Pallez, D., Precioso, F.: Hybrid Content Based Image Retrieval combining Multi-objective Interactive Genetic Algorithm and SVM. In: 21st International Conference on Pattern Recognition (ICPR), pp. 2849–2852, (2012).

    Google Scholar 

  8. Ligade, A.N., Patil, M.R.: Content Based Image Retrieval Using Interactive Genetic Algorithm with Relevance Feedback Technique—Survey. In: International Journal of Computer Science and Information Technologies, IJCSIT, pp. 5610–5613, (2014).

    Google Scholar 

  9. [Online] “Wang Database”, (2015) Available: http://wang.ist.psu.edu/docs/related/

  10. Jia Li, James Z. Wang: Automatic linguistic indexing of pictures by a statistical modeling approach. In: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.25 No.9. pp. 1075–1088. (2003).

    Google Scholar 

  11. Giorgio, G.: A Nearest Neighbor Approach to Relevance Feedback in Content Based Image Retrieval. In: 6th ACM International Conference on Image and Video Retrieval, CIVR’07, pp. 456–563, (2007).

    Google Scholar 

  12. Gali, R., Dewal, M.L., Anand, R.S.: Genetic Algorithm for Content Based Image Retrieval. In: 4th International Conference on Computational Intelligence, Communication Systems and Networks (CICSyN), IEEE, pp. 243–247, (2012).

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science & Engineering, ASET, Amity University, Noida, Uttar Pradesh, India

    Kavita Chauhan & Shanu Sharma

Authors
  1. Kavita Chauhan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shanu Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kavita Chauhan .

Editor information

Editors and Affiliations

  1. Department of Computer Science Engineering, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, India

    Suresh Chandra Satapathy

  2. Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  3. University of Hyderabad, Hyderabad, India

    Siba K. Udgata

  4. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer India

About this paper

Cite this paper

Kavita Chauhan, Sharma, S. (2016). Analysis and Optimization of Feature Extraction Techniques for Content Based Image Retrieval. In: Satapathy, S., Mandal, J., Udgata, S., Bhateja, V. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 435. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2757-1_36

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-2757-1_36

  • Published:

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2756-4

  • Online ISBN: 978-81-322-2757-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation