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| Performance Comparison of Image Retrieval Using Fractional Coefficients of Transformed Image Using DCT, Walsh, Haar and Kekre’s Transform
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Full
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Source |
International Journal of Image Processing (IJIP) |
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Table of Contents |
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Complete Issue PDF(13.48MB) |
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Volume: 4 Issue: 2 |
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Pages: 89-191 |
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Publication
Date: May 2010 |
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ISSN
(Online): 1985-2304 |
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Pages |
142 - 155 |
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Author(s) |
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Published
Date |
10-06-2010 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
Colleague |
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KEYWORDS: CBIR, Discrete Cosine Transform (DCT), Walsh Transform, Haar Transform, Kekre’s Transform, Fractional Coefficients |
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| The thirst of better and faster retrieval techniques has always fuelled to the research in content based image retrieval (CBIR). The paper presents innovative content based image retrieval (CBIR) techniques based on feature vectors as fractional coefficients of transformed images using Discrete Cosine, Walsh, Haar and Kekre’s transforms. Here the advantage of energy compaction of transforms in higher coefficients is taken to greatly reduce the feature vector size per image by taking fractional coefficients of transformed image. The feature vectors are extracted in fourteen different ways from the transformed image, with the first being considering all the coefficients of transformed image and then fourteen reduced coefficients sets (as 50%, 25%, 12.5%, 6.25%, 3.125%, 1.5625% ,0.7813%, 0.39%, 0.195%, 0.097%, 0.048%, 0.024%, 0.012% and 0.06% of complete transformed image) are considered as feature vectors. The four transforms are applied on gray image equivalents and the colour components of images to extract Gray and RGB feature sets respectively. Instead of using all coefficients of transformed images as feature vector for image retrieval, these fourteen reduced coefficients sets for gray as well as RGB feature vectors are used, resulting into better performance and lower computations. The proposed CBIR techniques are implemented on a database having 1000 images spread across 11 categories. For each proposed CBIR technique 55 queries (5 per category) are fired on the database and net average precision and recall are computed for all feature sets per transform. The results have shown performance improvement (higher precision and recall values) with fractional coefficients compared to complete transform of image at reduced computations resulting in faster retrieval. Finally Kekre’s transform surpasses all other discussed transforms in performance with highest precision and recall values for fractional coefficients (6.25% and 3.125% of all coefficients) and computation are lowered by 94.08% as compared to DCT. |
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H.B.Kekre, Sudeep D. Thepade, “Improving the Performance of Image Retrieval using Partial Coefficients of Transformed Image”, International Journal of Information Retrieval (IJIR), Serials Publications, Volume 2, Issue 1, 2009, pp. 72-79(ISSN: 0974-6285)
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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. ConceicaoRodrigous College of Engg., Mumbai. Is uploaded on online ACM portal.
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H.B.Kekre, Sudeep D. Thepade, “Scaling Invariant Fusion of Image Pieces in Panorama Making and Novel Image Blending Technique”, International Journal on Imaging (IJI), www.ceser.res.in/iji.html, Volume 1, No. A08, pp. 31-46, Autumn 2008.
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Hirata K. and Kato T. “Query by visual example – content-based image retrieval”, In Proc. of Third International Conference on Extending Database Technology, EDBT’92, 1992, pp 56-71
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H.B.Kekre, Sudeep D. Thepade, “Rendering Futuristic Image Retrieval System”, National Conference on Enhancements in Computer, Communication and Information Technology, EC2IT-2009, 20-21 Mar 2009, K.J.Somaiya College of Engineering, Vidyavihar, Mumbai-77.
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Minh N. Do, Martin Vetterli, “Wavelet-Based Texture Retrieval Using Generalized Gaussian Density and Kullback-Leibler Distance”, IEEE Transactions On Image Processing, Volume 11, Number 2, pp.146-158, February 2002.
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B.G.Prasad, K.K. Biswas, and S. K. Gupta, “Region –based image retrieval using integrated color, shape, and location index”, International Journal on Computer Vision and Image Understanding Special Issue: Colour for Image Indexing and Retrieval, Volume 94, Issues 1-3, April-June 2004, pp.193-233.
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H.B.Kekre, Sudeep D. Thepade, “Creating the Color Panoramic View using Medley of Grayscale and Color Partial Images ”, WASET International Journal of Electrical, Computer and System Engineering (IJECSE), Volume 2, No. 3, Summer 2008. Available online at www.waset.org/ijecse/v2/v2-3-26.pdf.
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Stian Edvardsen, “Classification of Images using color, CBIR Distance Measures and Genetic Programming”, Ph.D. Thesis, Master of science in Informatics, Norwegian university of science and Technology, Department of computer and Information science, June 2006.
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H.B.Kekre, Tanuja Sarode, Sudeep D. Thepade, “DCT Applied to Row Mean and Column Vectors in Fingerprint Identification”, In Proceedings of International Conference on Computer Networks and Security (ICCNS), 27-28 Sept. 2008, VIT, Pune.
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Zhibin Pan, Kotani K., Ohmi T., “Enhanced fast encoding method for vector quantization by finding an optimally-ordered Walsh transform kernel”, ICIP 2005, IEEE International Conference, Volume 1, pp I - 573-6, Sept. 2005.
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H.B.kekre, Sudeep D. Thepade, “Improving ‘Color to Gray and Back’ using Kekre’s LUV Color Space”, IEEE International Advanced Computing Conference 2009 (IACC’09), Thapar University, Patiala, INDIA, 6-7 March 2009. Is uploaded and available online at IEEE Xplore.
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H.B.Kekre, Sudeep D. Thepade, “Image Blending in Vista Creation using Kekre's LUV Color Space”, SPIT-IEEE Colloquium and International Conference, Sardar Patel Institute of Technology, Andheri, Mumbai, 04-05 Feb 2008.
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H.B.Kekre, Sudeep D. Thepade, “Color Traits Transfer to Grayscale Images”, In Proc.of IEEE First International Conference on Emerging Trends in Engg. & Technology, (ICETET-08), G.H.Raisoni COE, Nagpur, INDIA. Uploaded on online IEEE Xplore.
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http://wang.ist.psu.edu/docs/related/Image.orig (Last referred on 23 Sept 2008)
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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.
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H.B.Kekre, Sudeep D. Thepade, ArchanaAthawale, Anant Shah, PrathmeshVerlekar, SurajShirke,“Energy Compaction and Image Splitting for Image Retrieval using Kekre Transform over Row and Column Feature Vectors”, International Journal of Computer Science and Network Security (IJCSNS),Volume:10, Number 1, January 2010, (ISSN: 1738-7906) Available at www.IJCSNS.org.
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H.B.Kekre, Sudeep D. Thepade, ArchanaAthawale, Anant Shah, PrathmeshVerlekar, SurajShirke,“Walsh Transform over Row Mean and Column Mean using Image Fragmentation and Energy Compaction for Image Retrieval”, International Journal on Computer Science and Engineering (IJCSE),Volume 2S, Issue1, January 2010, (ISSN: 0975–3397). Available online at www.enggjournals.com/ijcse.
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H.B.Kekre, Sudeep D. Thepade,“Image Retrieval using Color-Texture Features Extracted from Walshlet Pyramid”, ICGST International Journal on Graphics, Vision and Image Processing (GVIP), Volume 10, Issue I, Feb.2010, pp.9-18, Available online www.icgst.com/gvip/Volume10/Issue1/P1150938876.html
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H.B.Kekre, Sudeep D. Thepade,“Color Based Image Retrieval using Amendment Block Truncation Coding with YCbCrColor Space”, International Journal on Imaging (IJI), Volume 2, Number A09, Autumn 2009, pp. 2-14. Available online at www.ceser.res.in/iji.html (ISSN: 0974-0627).
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H.B.Kekre, Tanuja Sarode, Sudeep D. Thepade,“Color-Texture Feature based Image Retrieval using DCT applied on Kekre’s Median Codebook”, International Journal on Imaging (IJI), Volume 2, Number A09, Autumn 2009,pp. 55-65. Available online at www.ceser.res.in/iji.html (ISSN: 0974-0627).
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H.B.Kekre, Sudeep D. Thepade, “Image Retrieval using Non-Involutional Orthogonal Kekre’s Transform”, International Journal of Multidisciplinary Research and Advances in Engineering (IJMRAE), Ascent Publication House, 2009, Volume 1, No.I, pp 189-203, 2009. Abstract available online at www.ascent-journals.com (ISSN: 0975-7074)
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H.B.Kekre, Sudeep D. Thepade, “Boosting Block Truncation Coding using Kekre’s LUV Color Space for Image Retrieval”, WASET International Journal of Electrical, Computer and System Engineering (IJECSE), Volume 2, Number 3, pp. 172-180, Summer 2008. Available online at http://www.waset.org/ijecse/v2/v2-3-23.pdf
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H.B.Kekre, Sudeep D. Thepade, Archana Athawale, Anant Shah, Prathmesh Verlekar, Suraj Shirke, “Performance Evaluation of Image Retrieval using Energy Compaction and Image Tiling over DCT Row Mean and DCT Column Mean”, Springer-International Conference on Contours of Computing Technology (Thinkquest-2010), BabasahebGawde Institute of Technology, Mumbai, 13-14 March 2010, The paper will be uploaded on online Springerlink.
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H.B.Kekre, Tanuja K. Sarode, Sudeep D. Thepade, VaishaliSuryavanshi,“Improved Texture Feature Based Image Retrieval using Kekre’s Fast Codebook Generation Algorithm”, Springer-International Conference on Contours of Computing Technology (Thinkquest-2010), BabasahebGawde Institute of Technology, Mumbai, 13-14 March 2010, The paper will be uploaded on online Springerlink.
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H.B.Kekre, Tanuja K. Sarode, Sudeep D. Thepade, “Image Retrieval by Kekre’s Transform Applied on Each Row of Walsh Transformed VQ Codebook”, (Invited), ACM-International Conference and Workshop on Emerging Trends in Technology (ICWET 2010),Thakur College of Engg. And Tech., Mumbai, 26-27 Feb 2010, The paper is invited at ICWET 2010. Also will be uploaded on online ACM Portal.
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H.B.Kekre, Sudeep D. Thepade, AkshayMaloo, “Image Retrieval using Fractional Coefficients of Transformed Image using DCT and Walsh Transform”, IJEST.
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| 28 |
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Charles K. Chui, “An Introduction to Wavelets”, Academic Press, 1992, San Diego, ISBN 0585470901.
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H. B. Kekre, Tanuja K. Sarode, V. A. Bharadi, A. Agrawal. R. Arora,, M. Nair, “Performance Comparison of Full 2-D DCT, 2-D Walsh and 1-D Transform over Row Mean and Column Mean for Iris Recognition” International Conference and Workshop on Emerging Trends in Technology (ICWET 2010) – 26-27 February 2010, TCET, Mumbai, India.
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M.C. Padma,P. A. Vijaya, “Wavelet Packet Based Features for Automatic Script Identification”, International Journal Of Image Processing (IJIP), CSC Journals, 2009, Volume 4, Issue 1, Pg.53-65.
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| 1 |
Dr. H.B.Kekre, S. D. Thepade, A. Maloo."CBIR Feature Vector Dimension Reduction with Eigenvectors of Covariance Matrix using Row, Column and Diagonal Mean Sequences".International Journal of Computer Applications, 3(12):39–46, 2010
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Dr. H. B. Kekre, T. Sarode, S. Natu, P. Natu. "Performance Comparison Of 2-D DCT On Full/Block Spectrogram And 1-D DCT On Row Mean Of Spectrogram For Speaker Identification".International Journal of Biometrics and Bioinformatics(IJBB), 4(3):100-112
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H.B.Kekre, D. Mishra."Performance Comparison of Density Distribution and Sector mean of sal and cal functions in Walsh Transform Sectors as Feature Vectors for Image Retrieval". International Journal Of Image Processing (IJIP), 4(3): 205-217
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Faculty of Mukesh Patel School of Technology Management & Engineering (MPSTME) - Narsee Monjee Institute of Management Studies (NMIMS)
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| H. B. Kekre : Colleagues
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| Sudeep D. Thepede : Colleagues
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| Akshay Maloo : Colleagues
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