CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

A Collaborative Approach to Enhance CBIR Performance using DCT, DST and Kekre's Transform

by Avanish Tiwari, Anurag Jain
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 114 - Number 18
Year of Publication: 2015
Authors: Avanish Tiwari, Anurag Jain
10.5120/20076-2099

Avanish Tiwari, Anurag Jain . A Collaborative Approach to Enhance CBIR Performance using DCT, DST and Kekre's Transform. International Journal of Computer Applications. 114, 18 ( March 2015), 6-11. DOI=10.5120/20076-2099

@article{ 10.5120/20076-2099,
author = { Avanish Tiwari, Anurag Jain },
title = { A Collaborative Approach to Enhance CBIR Performance using DCT, DST and Kekre's Transform },
journal = { International Journal of Computer Applications },
issue_date = { March 2015 },
volume = { 114 },
number = { 18 },
month = { March },
year = { 2015 },
issn = { 0975-8887 },
pages = { 6-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume114/number18/20076-2099/ },
doi = { 10.5120/20076-2099 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:53:06.583504+05:30
%A Avanish Tiwari
%A Anurag Jain
%T A Collaborative Approach to Enhance CBIR Performance using DCT, DST and Kekre's Transform
%J International Journal of Computer Applications
%@ 0975-8887
%V 114
%N 18
%P 6-11
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Content based Image retrieval is a process which will enhance the image searching accuracy. Many researchers are working on image processing. CBIR approach uses different techniques such as colour, texture and shape, by processing this feature vector is generated and comparison is done. CBIR approach can be used in many places such as search engines, patent registration, face detection etc. CBIR approach can also be used for security. It can encrypt and decrypt the image content to provide security. Stenography along with CBIR can generate algorithm which makes data more secure. CBIR can help in many fields only by referring image content. In this paper new approach "Hybrid approach" is implemented. Hybrid approach is a combination of different transforms. Combination of DCT, DST and kekre's transforms are used for feature vector generation. For image matching and distance calculation, two methods are used in this paper known as Euclidian distance and absolute distance method. In this paper, different transforms are combined to generate a hybrid approach. Results of different hybrid approaches are compared in this paper. It includes comparison of all the algorithms based on their performance by comparing different performance parameters such as precision and recall to determine which algorithm is providing the best 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.
  10. Sharma, Neetu S. , Paresh S. Rawat, and Jaikaran S. Singh. "Efficient CBIR using color histogram processing. " Signal & Image Processing 2, no. 1 (2011).
  11. 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.
  12. Yan, Chunlai. "Accurate Image Retrieval Algorithm Based on Color and Texture Feature. " Journal of Multimedia 8, no. 3 (2013): 277-283.
  13. Gupta, Vaibhav, and Anil Ramawat. "EVALUATION OF CBIR APPROACHES FOR DIFFERENTLY SIZED IMAGES. " International Journal on Computer Science and Engineering 4, no. 1 (2012).
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. 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).
  20. 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.
  21. 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 Hybrid transform Collaborative transform combining different transforms

Powered by PhDFocusTM