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Reseach Article

Article:Performance Comparison of Sectorization of DCT and DCT Wavelet Transformed Images in CBIR

by Dr. H.B.Kekre, Dhirendra Mishra
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 23 - Number 4
Year of Publication: 2011
Authors: Dr. H.B.Kekre, Dhirendra Mishra
10.5120/2876-3739

Dr. H.B.Kekre, Dhirendra Mishra . Article:Performance Comparison of Sectorization of DCT and DCT Wavelet Transformed Images in CBIR. International Journal of Computer Applications. 23, 4 ( June 2011), 26-34. DOI=10.5120/2876-3739

@article{ 10.5120/2876-3739,
author = { Dr. H.B.Kekre, Dhirendra Mishra },
title = { Article:Performance Comparison of Sectorization of DCT and DCT Wavelet Transformed Images in CBIR },
journal = { International Journal of Computer Applications },
issue_date = { June 2011 },
volume = { 23 },
number = { 4 },
month = { June },
year = { 2011 },
issn = { 0975-8887 },
pages = { 26-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume23/number4/2876-3739/ },
doi = { 10.5120/2876-3739 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:09:19.331402+05:30
%A Dr. H.B.Kekre
%A Dhirendra Mishra
%T Article:Performance Comparison of Sectorization of DCT and DCT Wavelet Transformed Images in CBIR
%J International Journal of Computer Applications
%@ 0975-8887
%V 23
%N 4
%P 26-34
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper mainly discusses the use of discrete cosine transform and its wavelet for feature extraction in the application of content based image retrieval. The proposed method has been experimented based on the concept of sectorization of the transformed images using DCT and DCT Wavelet. For the detailed study of the behavior of the method the sector sizes are varied in 4,8,12 and 16 sector sizes. For each sector sizes two separate similarity measures namely Euclidean distance (ED) and the sum of absolute difference (AD) are considered. So the performance of the proposed methods are compared and analyzed based on the sector sizes and type of similarity measures used. The various parameters like precision, recall and its cross over point plots, LIRS and LSRR are used to measure the overall as well as the class wise performances. The sizes of the image database consist of 1055 images distributed among 12 different classes. Comparing the performance of DCT and DCT Wavelet on the broader term it has been observed that 4 sectors and 8 sectors of DCT (column wise) and DCT Wavelet (column wise) with sum of Absolute difference as similarity measure provide the best outcome of the retrieval i.e. close to 45%.

References
  1. Kato, T., “Database architecture for content based image retrieval in Image Storage and Retrieval Systems” (Jambardino A and Niblack W eds),Proc SPIE 2185, pp 112-123, 1992.
  2. Ritendra Datta,Dhiraj Joshi,Jia Li and James Z. Wang, “ Image retrieval:Idea,influences and trends of the new age”,ACM Computing survey,Vol 40,No.2,Article 5,April 2008.
  3. John Berry and David A. Stoney “The history and development of fingerprinting,” in Advances in Fingerprint Technology, Henry C. Lee and R. E. Gaensslen, Eds., pp. 1-40. CRC Press Florida, 2nd edition, 2001.
  4. H.B.Kekre, Archana Athawale, Dipali sadavarti, “Algorithm to generate wavelet transform from an orthogonal transform”, International journal of Image processing, Vol.4(4), pp.444-455
  5. H. B. Kekre, Dhirendra Mishra, “Digital Image Search & Retrieval using FFT Sectors” published in proceedings of National/Asia pacific conference on Information communication and technology(NCICT 10) 5TH & 6TH March 2010.SVKM’S NMIMS MUMBAI
  6. H.B.Kekre, Dhirendra Mishra, “Content Based Image Retrieval using Weighted Hamming Distance Image hash Value” published in the proceedings of international conference on contours of computing technology pp. 305-309 (Thinkquest2010) 13th & 14th March 2010.
  7. H.B.Kekre, Dhirendra Mishra,“Digital Image Search & Retrieval using FFT Sectors of Color Images” published in International Journal of Computer Science and Engineering (IJCSE) Vol. 02,No.02,2010,pp.368-372 ISSN 0975-3397 available online at http://www.enggjournals.com/ijcse/doc/IJCSE10-02- 02-46.pdf
  8. H.B.Kekre, Dhirendra Mishra, “CBIR using upper six FFT Sectors of Color Images for feature vector generation” published in International Journal of Engineering and Technology(IJET) Vol. 02, No. 02, 2010, 49-54 ISSN 0975-4024 available online at http://www.enggjournals.com/ijet/doc/IJET10-02- 02-06.pdf
  9. H.B.Kekre, Dhirendra Mishra, “Four walsh transform sectors feature vectors for image retrieval from image databases”, published in international journal of computer science and information technologies (IJCSIT) Vol. 1 (2) 2010, 33-37 ISSN 0975-9646 available online at http://www.ijcsit.com/docs/vol1issue2/ijcsit2010010201.pdf
  10. H.B.Kekre, Dhirendra Mishra, “Performance comparison of four, eight and twelve Walsh transform sectors feature vectors for image retrieval from image databases”, published in international journal of Engineering, science and technology(IJEST) Vol.2(5) 2010, 1370-1374 ISSN 0975-5462 available online at http://www.ijest.info/docs/IJEST10-02-05-62.pdf
  11. H.B.Kekre, Dhirendra Mishra, “density distribution in walsh transfom sectors ass feature vectors for image retrieval”, published in international journal of compute applications (IJCA) Vol.4(6) 2010, 30-36 ISSN 0975-8887 available online at http://www.ijcaonline.org/archives/volume4/number6/829-1072
  12. H.B.Kekre, Dhirendra Mishra, “Performance comparison of density distribution and sector mean in Walsh transform sectors as feature vectors for image retrieval”, published in international journal of Image Processing (IJIP) Vol.4(3) 2010, ISSN 1985-2304 available online at http://www.cscjournals.org/csc/manuscript/Journals/IJIP/Volume4/Issue3/IJIP-193.pdf
  13. H.B.Kekre, Dhirendra Mishra, “Density distribution and sector mean with zero-sal and highest-cal components in Walsh transform sectors as feature vectors for image retrieval”, published in international journal of Computer scienece and information security (IJCSIS) Vol.8(4) 2010, ISSN 1947-5500 available online http://sites.google.com/site/ijcsis/vol-8-no-4-jul-2010
  14. Arun Ross, Anil Jain, James Reisman, “A hybrid fingerprint matcher,” Int’l conference on Pattern Recognition (ICPR), Aug 2002.
  15. A. M. Bazen, G. T. B.Verwaaijen, S. H. Gerez, L. P. J. Veelenturf, and B. J. van der Zwaag, “A correlation-based fingerprint verification system,” Proceedings of the ProRISC2000 Workshop on Circuits, Systems and Signal Processing, Veldhoven, Netherlands, Nov 2000.
  16. H.B.Kekre, Tanuja K. Sarode, Sudeep D. Thepade, “Image Retrieval using Color-Texture Features from DCT on VQ Codevectors obtained by Kekre’s Fast Codebook Generation”, ICGST International Journal on Graphics, Vision and Image Processing (GVIP), Available online at http://www.icgst.com/gvip
  17. H.B.Kekre, Sudeep D. Thepade, “Using YUV Color Space to Hoist the Performance of Block Truncation Coding for Image Retrieval”, IEEE International Advanced Computing Conference 2009 (IACC’09), Thapar University, Patiala, INDIA, 6-7 March 2009.
  18. H.B.Kekre, Sudeep D. Thepade, “Image Retrieval using Augmented Block Truncation Coding Techniques”, ACM International Conference on Advances in Computing, Communication and Control (ICAC3-2009), pp.: 384-390, 23-24 Jan 2009, Fr. Conceicao Rodrigous College of Engg., Mumbai. Available online at ACM portal.
  19. H.B.Kekre, Tanuja K. Sarode, Sudeep D. Thepade, “DCT Applied to Column mean and Row Mean Vectors of Image for Fingerprint Identification”, International Conference on Computer Networks and Security, ICCNS-2008, 27-28 Sept 2008, Vishwakarma Institute of Technology, Pune.
  20. H.B.Kekre, Sudeep Thepade, Archana Athawale, Anant Shah, Prathmesh Velekar, Suraj Shirke, “ Walsh transform over row mean column mean using image fragmentation and energy compaction for image retrieval”, International journal of computer science and engineering (IJCSE),Vol.2.No.1,S2010,47-54.
  21. H.B.Kekre, Vinayak Bharadi, “Walsh Coefficients of the Horizontal & Vertical Pixel Distribution of Signature Template”, In Proc. of Int. Conference ICIP-07, Bangalore University, Bangalore. 10-12 Aug 2007.
  22. H.B.Kekre, Dhirendra Mishra, “DCT Sectorization for feature vector generation in CBIR”, International journal of computer Applications (IJCA),Vol.9,No.1,pp.19-26
  23. H.B.Kekre, Dhirendra Mishra, “DST Sectorization for Feature vector generation”, Universal journal of computer science and and Engineering Technology (UniCSE),Vol.1, No.1, Oct.2010,pp.6-15,Available online at http://www.unicse.org/index.php?option=com_content&view=article&id=54&Itemid=27
  24. H.B.Kekre, Dhirendra Mishra, “DCT-DST Plane sectorization of row wise transformed color images in CBIR”, International journal of engineering science and technology, Vol.2, No.12, Dec.2010, pp.7234-7244, ISSN No.0975-5462. Available at http://www.ijest.info/docs/IJEST10-02-12-143.pdf
  25. 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, http://sites.google.com/site/ijcsis/volume-9-no-2-feb-2011
  26. H.B.Kekre, Dhirendra Mishra, “Sectorization of Kekre’s transform for image retrieval in content based image retrieval”, Journal of Telecommunication (JOT),UK, Vol.8, No.1 April 2011, pp. 26-33. http://sites.google.com/site/journaloftelecommunications/volume-8-issue-1-april-2011
  27. H.B.Kekre, Dhirendra Mishra, “Sectorization of DCT- DST Plane for column wise transformed color images in CBIR”, International Conference of Technology Systems & Management (ICTSM-2011) held at SVKM’s NMIMS Mumbai India, published in Springer Link CCIS 145, pp. 55–60, 2011. Available online at http://www.springerlink.com/content/m573256n53r07733/
  28. H.B.Kekre, Dhirendra Mishra, “Full DCT sectorization for Feature vector generation in CBIR”, Journal of graphics, vision, image processing, Vol.11, No.2, April 2011, pp. 19 – 30 http://www.icgst.com/gvip/Volume11/Issue2/P1151041315.html
  29. Jia Li, James Z. Wang, ``Automatic linguistic indexing of pictures by a statistical modeling approach,'' IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 9, pp. 1075-1088, 2003.
Index Terms

Computer Science
Information Sciences

Keywords

CBIR Precision Recall LSRR LIRS Euclidean distance sum of absolute difference