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Content based Image Retrieval Review on its Methods and Transforms

by Avanish Tiwari, Anurag Jain
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 102 - Number 14
Year of Publication: 2014
Authors: Avanish Tiwari, Anurag Jain
10.5120/17885-8852

Avanish Tiwari, Anurag Jain . Content based Image Retrieval Review on its Methods and Transforms. International Journal of Computer Applications. 102, 14 ( September 2014), 33-40. DOI=10.5120/17885-8852

@article{ 10.5120/17885-8852,
author = { Avanish Tiwari, Anurag Jain },
title = { Content based Image Retrieval Review on its Methods and Transforms },
journal = { International Journal of Computer Applications },
issue_date = { September 2014 },
volume = { 102 },
number = { 14 },
month = { September },
year = { 2014 },
issn = { 0975-8887 },
pages = { 33-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume102/number14/17885-8852/ },
doi = { 10.5120/17885-8852 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:33:22.897882+05:30
%A Avanish Tiwari
%A Anurag Jain
%T Content based Image Retrieval Review on its Methods and Transforms
%J International Journal of Computer Applications
%@ 0975-8887
%V 102
%N 14
%P 33-40
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

CBIR (content based image retrieval) is the process which mainly focuses to provide efficient retrieval of digital image from the huge collection/database of the images. As many researchers and PhD scholars are working on this topic. So in this paper many algorithms have been studied and discussed such as sectorization of DCT-DST Plane of Row wise transform, discrete sine transform sectorization for feature vector generation, FFT sectorization for feature vector generation, histogram matching, histogram bins. This paper also includes the different filtering techniques like median filter, point operator and histogram normalization techniques. It includes comparison of all the algorithms based on their performance by comparing different performance parameters such as LIRS (Length of initial string of relevant images retrieved), LSRR (Length of string to recover all relevant images) and LSRI (Longest string of relevant images retrieved), precision and recall to determine which algorithm is providing best result. Based on all comparison this paper concludes that Column wise walsh wavelet transform gives best result. It gives 40% precision values but LSRR result is more than 60%. So as per the results it is stated that hybrid approach will give better result.

References
  1. H. B. Kekre, Dhirendra Mishra, "DCT Sectorization for Feature Vector Generation in CBIR" International Journal of Computer Applications (0975 – 8887) Volume 9– No. 1, November 2010.
  2. H. B. Kekre, Dhirendra Mishra, "DCT-DST Plane sectorizationof Row-wise Transformed color Images in CBIR", International Journal of Engineering Science and Technology Vol. 2 (12), 2010, 7234-7244.
  3. H. B. Kekre, Dhirendra Mishra, ChiragThakkar, "Column wise DCT plane sectorization in CBIR," International Journal of Computer Science and Information Technologies (IJCSIT), vol. 3 no. 1, pp. 3229-3235, 2012.
  4. H. B. Kekre, Kamal Shah, "Application of DCT row and column feature vector for face recognition with comparison to full DCT and PCA", International Journal of Computer Applications in Engineering, Technology and Science (IJ-CA-ETS) , Vol. 1, No. 2, 435-439 April/September 2009.
  5. Dr. H. B. Kekre, Dhirendra Mishra, "Sectorization of Walsh and Walsh Wavelet in CBIR", International Journal on Computer Science and Engineering (IJCSE) Vol. 3 No. 6 June 2011.
  6. H. B. Kekre, Dhirendra Mishra, "Sectorization of Haar and Kekre's Wavelet for feature extraction of color images in image retrieval", International journal of computer science and information security (IJCSIS), USA, Vol. 9, No. 2, Feb 2011, pp. 180-188.
  7. Rui, Yong, Thomas S. Huang, and Shih-Fu Chang. "Image retrieval: Current techniques, promising directions, and open issues. " Journal of visual communication and image representation 10, no. 1 (1999): 39-62.
  8. Mandal, Mrinal K. , F. Idris, and Sethuraman Panchanathan. "A critical evaluation of image and video indexing techniques in the compressed domain. " Image and Vision Computing 17, no. 7 (1999): 513-529.
  9. Sharma, Neetu S. , Paresh S. Rawat, and Jaikaran S. Singh. "Efficient CBIR using color histogram processing. " Signal & Image Processing 2, no. 1 (2011).
  10. Jain, Monika, and S. K. Singh. "A survey on: content based image retrieval systems using clustering techniques for large data sets. " International Journal of Managing Information Technology (IJMIT) 3, no. 4 (2011): 23-39.
  11. Yan, Chunlai. "Accurate Image Retrieval Algorithm Based on Color and Texture Feature. " Journal of Multimedia 8, no. 3 (2013): 277-283.
  12. Gupta, Vaibhav, and Anil Ramawat. "EVALUATION OF CBIR APPROACHES FOR DIFFERENTLY SIZED IMAGES. " International Journal on Computer Science and Engineering 4, no. 1 (2012).
  13. Datta, Ritendra, Dhiraj Joshi, Jia Li, and James Z. Wang. "Image retrieval: Ideas, influences, and trends of the new age. " ACM Computing Surveys (CSUR) 40, no. 2 (2008): 5.
  14. Tamura, Hideyuki, Shunji Mori, and Takashi Yamawaki. "Textural features corresponding to visual perception. " Systems, Man and Cybernetics, IEEE Transactions on 8, no. 6 (1978): 460-473.
  15. Smeulders, Arnold WM, Marcel Worring, Simone Santini, Amarnath Gupta, and Ramesh Jain. "Content-based image retrieval at the end of the early years. " Pattern Analysis and Machine Intelligence, IEEE Transactions on 22, no. 12 (2000): 1349-1380.
  16. Kekre, Dr HB, Sudeep D. Thepade, and Akshay Maloo. "Query by Image Content Using Colour Averaging Techniques. " Engineering journals, International Journal of Engineering, Science and Technology (IJEST) 2, no. 6 (2010): 1612-1622.
  17. Kekre, H. B. , and Sudeep D. Thepade. "Rendering Futuristic Image Retrieval System. " In National Conference on Enhancements in Computer, Communication and Information Technology, EC2IT-2009, pp. 20-21. 2009.
  18. Khokher, Amandeep, and Dr Rajneesh Talwar. "Image Retrieval: A State Of The Art Approach For Cbir. " International Journal Of Engineering Science And Technology (IJEST) (2011).
  19. Shriram, K. V. , P. L. K. Priyadarsini, and V. Subashri. "An Efficient and Generalized approach for Content Based Image Retrieval in MatLab. " International Journal of Image, Graphics and Signal Processing (IJIGSP) 4, no. 4 (2012): 42.
  20. Kekre, H. B. , Sudeep D. Thepade, and Akshay Maloo. "Performance Comparison of Image Retrieval Using Fractional Coefficients of Transformed Image Using DCT, Walsh, Haar and Kekre's Transform. " CSC-International Journal of Image processing (IJIP) 4, no. 2 (2010): 142-155.
Index Terms

Computer Science
Information Sciences

Keywords

CBIR Feature Vector Transform Sectorization Spatial Domain Frequency Domain Similarity Measures