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Performance Comparison of Density Distribution and Sector mean of sal and cal functions in Walsh Transform Sectors as Feature Vectors for Image Retrieval
H. B. Kekre, Dhirendra Mishra
Pages - 205 - 217     |    Revised - 30-06-2010     |    Published - 10-08-2010
Volume - 4   Issue - 3    |    Publication Date - July 2010  Table of Contents
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KEYWORDS
CBIR, Precision and Recall, Eucledian Distance, Kekre's Algorithm, Walsh Transform
ABSTRACT
In this paper we have proposed two different approaches for feature vector generation with absolute difference as similarity measuring parameter. Sal-cal vectors density distribution and Individual sector mean of complex Walsh transform. The cross over point performance of overall average of precision and recall for both approaches on all applicable sectors sizes are compared. The complex Walsh transform is conceived by multiplying sal components by j= ã-1. The density distribution of real (cal) and imaginary (sal) values and individual mean of Walsh sectors in all three color planes are considered to design the feature vector. The algorithm proposed here is worked over database of 270 images spread over 11 different classes. Overall Average precision and recall is calculated for the performance evaluation and comparison of 4, 8, 12 & 16 Walsh sectors. The overall average of cross over points of precision and recall is of all methods for both approaches are compared. The use of Absolute difference as similarity measure always gives lesser computational complexity and Individual sector mean approach of feature vector has the best retrieval.
CITED BY (7)  
1 Kekre, H. B., Sarode, T., & Halarnkar, P. N. (2016). Partial Image Scrambling Using Walsh Sequency in Sinusoidal Wavelet Transform Domain. In Intelligent Systems Technologies and Applications (pp. 471-484). Springer International Publishing.
2 Kekre, H. B., Mishra, D., & Desai, V. (2014, March). Detection of defective pharmaceutical capsules and its types of defect using image processing techniques. In Circuit, Power and Computing Technologies (ICCPCT), 2014 International Conference on (pp. 1190-1195). IEEE.
3 Kulkarni, V. (2013). Speaker identification using orthogonal transforms and vector quantization.
4 Kekre, H. B., Mishra, D., & Kariwala, A. (2011). A survey of CBIR techniques and semantics. International Journal of Engineering Science and Technology, 3(5).
5 Kekre, H. B., & Kulkarni, V. (2011, February). Automatic speaker recognition using circular DFT sectors. In Proceedings of the International Conference & Workshop on Emerging Trends in Technology (pp. 1280-1285). ACM.
6 Kekre, H. B., & Kulkarni, V. (2011). Performance Comparison of Speaker Identification using circular DFT and WHT Sectors. International Journal of Computer Science and Information Security, 9(3), 139.
7 Kulkarni, V. HB Kekre Vaishali Kulkarni.
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1 Anil Jain, Arun Ross, Salil Prabhakar, “Fingerprint matching using minutiae and texture features,” Int’l conference on Image Processing (ICIP), pp. 282-285, Oct. 2001.
2 Kato, T., “Database architecture for content-basedimage retrieval in Image Storage and Retrieval Systems” (Jambardino A and Niblack W eds),Proc SPIE 2185, pp 112-123, 1992.
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 Emma Newham, “The biometric report,” SJB Services, 1995.
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 8. 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 Arun Ross, Anil Jain, James Reisman, “A hybrid fingerprint matcher,” Int’l conference on Pattern Recognition (ICPR), Aug 2002.
10 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.
11 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
12 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.
13 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.
14 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.
15 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
16 H.B.Kekre, Kavita sonawane, “DCT Over Color Distribution of Rows and Columns of Images for CBIR” SANSHODHAN, SFIT Technical Magazine No 5, pp. 11-17, March2010.
17 H.B.Kekre, Tanuja Sarode, “Two Level Vector Quantization Method for Codebook Generation using Kekre’s Proportionate Error Algorithm” International Journal of Image Processing, Vol.4, Issue 1, pp.1-10, January-February 2010 .
18 Dr. H. B. Kekre, Sudeep D. Thepade, Akshay Maloo, “ Performance Comparison of Image Retrieval Using Fractional Coefficients of Transformed Image Using DCT, Walsh, Haar and Kekre’s Transform”, International Journal of Image Processing, Vol.4, Issue 2, pp.142-155, March-April 2010.
19 Hiremath P.S, Jagadeesh Pujari, “Content Based Image Retrieval using Color Boosted Salient Points and Shape features of an image”, International Journal of Image Processing (IJIP) Vol.2, Issue 1, pp 10-17, January-February 2008.
Dr. H. B. Kekre
MPSTME,NMIMS University - India
hbkekre@yahoo.com
Mr. Dhirendra Mishra
MPSTME,NMIMS University - India