Comparison of Various Feature Extraction Techniques in CBIR using Statistical Parameters

H. B. Kekre; Aditi Mehta; Paulami Shah

Research Article

Comparison of Various Feature Extraction Techniques in CBIR using Statistical Parameters

by H. B. Kekre, Aditi Mehta, Paulami Shah

International Journal of Computer Applications

Foundation of Computer Science (FCS), NY, USA

Volume 93 - Issue 18

Published: May 2014

Authors: H. B. Kekre, Aditi Mehta, Paulami Shah

10.5120/16432-5600

PDF

H. B. Kekre, Aditi Mehta, Paulami Shah . Comparison of Various Feature Extraction Techniques in CBIR using Statistical Parameters. International Journal of Computer Applications. 93, 18 (May 2014), 1-6. DOI=10.5120/16432-5600

                        @article{ 10.5120/16432-5600,
                        author  = { H. B. Kekre,Aditi Mehta,Paulami Shah },
                        title   = { Comparison of Various Feature Extraction Techniques in CBIR using Statistical Parameters },
                        journal = { International Journal of Computer Applications },
                        year    = { 2014 },
                        volume  = { 93 },
                        number  = { 18 },
                        pages   = { 1-6 },
                        doi     = { 10.5120/16432-5600 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }

                        %0 Journal Article
                        %D 2014
                        %A H. B. Kekre
                        %A Aditi Mehta
                        %A Paulami Shah
                        %T Comparison of Various Feature Extraction Techniques in CBIR using Statistical Parameters%T 
                        %J International Journal of Computer Applications
                        %V 93
                        %N 18
                        %P 1-6
                        %R 10.5120/16432-5600
                        %I Foundation of Computer Science (FCS), NY, USA

Abstract

In fields such as medical, art galleries, museums, archaeology, medical imaging, trademark databases, criminal investigations, images especially the digital images grow in quantities of thousands and sometimes even lakhs every year. Content based image retrieval is required from such large databases. This paper compares Statistical Parameters based CBIR techniques based on the performance evaluation parameters namely, precision, recall, LIRS and LSRR. Minkowski Distance is used for the purpose of similarity measure.

References

H. B. Kekre, Sudeep D. Thepade, "Boosting Block Truncation CodingusingKekre'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.
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. ConceicaoRodrigousCollegeofEngg. , Mumbai. Is uploaded on online ACM portal.
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.
Hirata K. and Kato T. "Query by visual example – content-based image retrieval", In Proc. of Third International Conference on H Extending Database Technology, EDBT'92, 1992, pp 56-71
H. B. Kekre, Sudeep D. Thepade, "Rendering Futuristic Image RetrievalSystem", National Conference on Enhancements in Computer,Communication and Information Technology, EC2IT-2009, 20-21 Mar2009, K. J. Somaiya College of Engineering, Vidyavihar, Mumbai-77
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.
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.
Dr. H. B. Kekre, Dr. Dhirendra Mishra, " DCT Sectorization for Feature Vector Generation in CBIR",International Journal of Computer Applications (IJCA) Vol. 9(1) November 2010, ISSN 0975–8887 available online at http://www. ijcaonline. org/volume9/number1/pxc3871820. pdf
Dr. H. B. Kekre, Dr. Dhirendra Mishra, "DCT-DST Plane sectorization of Row-wise Transformed color Images in CBIR",International Journal of Engineering Science and Technology (IJEST) Vol. 2(12) 2010, ISSN 7234-7244available online at http://nmims. edu/wp-content/uploads/2012/p3/MPSTME/Direndra,DCT-DSTPlanesectorization. pdf
Dr. H. B. Kekre, Dhirendra Mishra, " Density distribution in WalshTransform sectors as 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
Dr. H. B. Kekre, SudeepDThepade, AkshayMaloo, "Query by Image Content Using Colour Averaging Techniques", International Journal of Engineering Science and Technology (IJEST), Volume 2, Issue 6, 2010. pp. 1612-1622 (ISSN: 0975-5462) Available online at http://www. ijest. info
Dr. H. B. Kekre, SudeepDThepade, AkshayMaloo, "Image Retrieval using Fractional Coefficients of Transformed Image using DCT and Walsh Transform", International Journal of Engineering Science and Technology (IJEST), Volume 2, Issue 4, 2010. pp. 362-371 (ISSN: 0975-5462) Available online at http://www. ijest. info
Dr. H. B. Kekre, SudeepDThepade, AkshayMaloo, "Performance Comparison of Image Retrieval using Row Mean of Transformed Column Image", International Journal of Engineering Science and Technology (IJEST), Volume 2, Issue 5, 2010. pp. 1908-1912 (ISSN: 0975-3397) Available online at http://www. ijest. info

Index Terms

Computer Science

Information Sciences

No index terms available.

Keywords

Content Based Image Retrieval(CBIR) Standard Deviation(SD) Precision Recall Length of Initial Relevant String of images(LIRS) Length of String required to Recover Relevant Images (LSRR) Minkowaski Distance (MD) Feature Vector(FV).