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Performance Comparison of Image Retrieval Using Fractional Coefficients of Transformed Image Using DCT, Walsh, Haar and Kekre’s Transform
H. B. Kekre, Sudeep D. Thepede, Akshay Maloo
Pages - 142 - 155     |    Revised - 30-04-2010     |    Published - 10-06-2010
Volume - 4   Issue - 2    |    Publication Date - May 2010  Table of Contents
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KEYWORDS
CBIR, Discrete Cosine Transform (DCT), Walsh Transform, Haar Transform, Kekre’s Transform, Fractional Coefficients
ABSTRACT
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.
CITED BY (41)  
1 Tiwari, A., & Jain, A. (2015). A Collaborative Approach to Enhance CBIR Performance using DCT, DST and Kekre's Transform. International Journal of Computer Applications, 114(18).
2 Przytulska, M., Kulikowski, J. L., & Wierzbicka, D. (2014). Biomedical images enhancement based on the properties of morphological spectra. Biocybernetics and Biomedical Engineering.
3 Chinnasamy, S. (2014). Performance improvement of fuzzy-based algorithms for medical image retrieval. IET Image Processing, 8(6), 319-326.
4 Thepade, S., & Mandal, P. R. (2014, December). Energy compaction based novel Iris recognition techniques using partial energies of transformed iris images with Cosine, Walsh, Haar, Kekre, Hartley Transforms and their Wavelet Transforms. In India Conference (INDICON), 2014 Annual IEEE (pp. 1-6). IEEE.
5 Thepade, D. S., & Mandal, P. R. (2014). Novel Iris Recognition Technique using Fractional Energies of Transformed Iris Images using Haar and Kekre Transforms. International Journal Of Scientific & Engineering Research, 5(4).
6 Sakpal, V. D., & Sakpal, V. (2013). Performance Comparison of Transform Techniques for Hand Gesture Recognition. International Journal of Advanced Research in Computer Science, 4(9).
7 Thepade, S. D., & Gudadhe, S. S. (2013, August). Fractional coefficients of transformed edge palm images with Cosine, Kekre and Slant wavelet transforms for palm print identification. In Advances in Computing, Communications and Informatics (ICACCI), 2013 International Conference on (pp. 698-703). IEEE.
8 Sarode, T. K., & Sakpal, V. D. (2013). Performance Comparison of Transforms using Row Mean and Column Mean for Hand Gesture Recognition. International Journal of Computer Applications, 78(9), 1-5.
9 Thepade, S. D., & Gudadhe, S. S. (2013, April). Palm print identification using fractional coefficient of transformed edge palm images with Cosine, Haar and Kekre transform. In Information & Communication Technologies (ICT), 2013 IEEE Conference on (pp. 1232-1236). IEEE.
10 Saraswat, M., Goswami, A. K., & Tiwari, A. (2013). Object Recognition Using Texture Based Analysis. International Journal of Computer Science and Information Technologies, 4(6), 775-782.
11 Kousalya, S., & Thananmani, A. S. (2013). Image Mining-Similar Image Retrieval Using Multi-Feature Extraction and Content Based Image Retrieval Technique. Image, 2(11).
12 Thepade, S. D., Das, R. K. K., & Ghosh, S. (2013). Image classification using advanced block truncation coding with ternary image maps. In Advances in Computing, Communication, and Control (pp. 500-509). Springer Berlin Heidelberg.
13 Herrero Bajo, S. (2012). Implementation of the Fisher Kernel Framework for image retrieval.
14 Sarode, T. K., & Patil, P. (2012). Comparing Transform Domain Techniques and Vector Quantization Techniques for Face Detection and Recognition in Digital Images. International Journal of Computer Applications, 49(4), 19-22.
15 Sarode, T. K., & Patil, P. (2012). Face Detection and Recognition in Digital Images using Transform Domain Techniques. International Journal of Computer Applications, 48(20), 12-15.
16 Padmaja, V. K., & Chandrasekhar, B. (2012). Literature review of image compression effects on face recognition. International Multidisciplinary Research Journal, 2(8), 17-20.
17 Chandrasekhar, B. Literature Review of Image Compression Algorithm.
18 Ayyildiz, K., & Conrad, S. Analyzing Transformation of 1D-Functions for Frequency Domain based Video Classification.
19 Layer, M. International Journal of Emerging Technologies in Computational and Applied Sciences (IJETCAS) www. iasir. net.
20 Kekre, H. B., Sarode, T. K., & Ugale, M. S. (2011). Performance Comparison of Image Classifier Using DCT, Walsh, Haar and Kekre's Transform. International Journal of Computer Science and Information Security, 9(7), 26.
21 Kekre, D. H., Thepade, D. S. D., & Maloo, A. (2011). Comprehensive performance comparison of Cosine, Walsh, Haar, Kekre, Sine, slant and Hartley transforms for CBIR with fractional coefficients of transformed image. International Journal of Image Processing (IJIP), 5(3), 336.
22 Kekre, H. B., Thepade, S. D., & Banura, V. K. (2011). Performance Comparison of Gradient Mask Texture Based Image Retrieval Techniques using Walsh, Haar and Kekre Transforms with Image Maps. International Journal of Computer Applications (IJCA), Special Issue July, 201(1).
23 Kekre, H. B., Sarode, T. K., Natu, P. J., & Natu, S. J. (2011). Performance Comparison of Face Recognition using DCT and Walsh Transform with Full and Partial Feature Vector against KFCG VQ Algorithm. threshold, 4, 29.
24 Kekre, H. B., Thepade, S. D., & Banura, V. K. (2011). Performance Comparison of Texture Pattern Based Image Retrieval Methods using Walsh, Haar and Kekre Transforms with Assorted Thresholding Methods. International Journal of Computer Science and Information Security, 9(3), 76.
25 Kekre, H. B., Sarode, T., & Ugale, M. S. (2011). Performance Comparison of Image Classifier using Discrete Cosine Transform and Walsh Transform. In IJCA Proceedings on International Conference and workshop on Emerging Trends in Technology (ICWET)(4) (pp. 14-20).
26 Padmanabhan, S. A., & Chandramathi, S. (2011, December). A proficient video encoding system through a novel motion estimation algorithm. In Advanced Computing (ICoAC), 2011 Third International Conference on (pp. 151-156). IEEE.
27 Kekre, H. B., Thepade, S. D., Viswanathan, A., Varun, A., Dhwoj, P., & Kamat, N. (2011). Palm print identification using fractional coefficients of Sine/Walsh/Slant transformed palm print images. In Technology Systems and Management (pp. 214-220). Springer Berlin Heidelberg.
28 Kekre11, H. B., Thepade, S. D., Banura, V. K., & Khandelwal, A. (2011). Introducing Global and Local Walsh Wavelet Transform for Texture Pattern Based Image Retrieval. IJCSNS, 11(9), 65.
29 Kekre, H. B., Sarode, T. K., & Ugale, M. S. (2011, February). An efficient image classifier using discrete cosine transform. In Proceedings of the International Conference & Workshop on Emerging Trends in Technology (pp. 330-337). ACM.
30 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
31 Kekre, H. B., Sarode, T. K., Natu, S. J., & Natu, P. J. (2010). 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.
32 Kekre, H. B., Thepade, S. D., Varun, A., Kamat, N., Viswanathan, A., & Dhwoj, P. (2010). Performance comparison of image transforms for palm print recognition with fractional coefficients of transformed palm print images. IJEST, 2(12),7372-7379.
33 Kekre, D. H., Thepade, S., Mukherjee, P., Kakaiya, M., Wadhwa, S., & Singh, S. (2010). Edge texture based CBIR using row mean of transformed column gradient image. International Journal of Computer Applications, 7(10), 12-17.
34 Kekre, H. B., Sarode, T., Natu, S. J., & Natu, P. J. (2010). Performance Comparison of Speaker Identification Using DCT, Walsh, Haar on Full and Row Mean of Spectrogram. International Journal of Computer Applications (0975–8887) Volume.
35 Kekre, D. H., Thepade, S., Mukherjee, P., Kakaiya, M., Wadhwa, S., & Singh, S. (2010). Image Retrieval with Shape Features Extracted using Morphological Operators with BTC. Image, 12(3).
36 Kekre, H. B., Sarode, T. K., Natu, S. J., & Natu, P. J. (1733). Speaker Identification Using 2-D DCT, Walsh And Haar On Full And Block Spectrogram. International Journal on Computer Science and Engineering, 2(5), 2010.
37 Kekre, H. B., & Mishra, D. (2010). 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.
38 Kekre, H. B., Sarode, T., Natu, P., & Natu, S. (2010, September). Performance Comparison of Face Recognition Using DCT Against Face Recognition Using Vector Quantization Algorithms. In LBG, KPE, KMCG, KFCG” International Journal Of Image Processing (IJIP.
39 Natu, S. J., Natu, P. J., Sarode, T. K., & Kekre, H. B. (2010). Performance Comparison of Face Recognition Using DCT Against Face Recognition Using Vector Quantization Algorithms LBG, KPE, KMCG, KFCG.
40 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
41 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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1 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)
2 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.
3 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.
4 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
5 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.
6 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.
7 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.
8 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.
9 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.
10 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.
11 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.
12 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.
13 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.
14 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.
15 http://wang.ist.psu.edu/docs/related/Image.orig (Last referred on 23 Sept 2008)
16 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.
17 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.
18 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.
19 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
20 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).
21 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).
22 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)
23 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
24 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.
25 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.
26 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.
27 H.B.Kekre, Sudeep D. Thepade, AkshayMaloo, “Image Retrieval using Fractional Coefficients of Transformed Image using DCT and Walsh Transform”, IJEST.
28 Haar, Alfred, “ZurTheorie der orthogonalenFunktionensysteme”. (German), MathematischeAnnalen, volume 69, No. 3, 1910, pp. 331–371.
29 Charles K. Chui, “An Introduction to Wavelets”, Academic Press, 1992, San Diego, ISBN 0585470901.
30 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.
31 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.
Dr. H. B. Kekre
- India
hbkekre@yahoo.com
Mr. Sudeep D. Thepede
- India
Mr. Akshay Maloo
- India