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Content Based Image Retrieval Using Full Haar Sectorization
H.B. Kekre, Dhirendra Mishra
Pages - 1 - 12     |    Revised - 31-03-2011     |    Published - 04-04-2011
Volume - 5   Issue - 1    |    Publication Date - March / April 2011  Table of Contents
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KEYWORDS
CBIR, Haar Wavelet, Euclidian Distance, Sum of Absolute Difference, LIRS and LSRR, Precision and Recall
ABSTRACT
Content based image retrieval (CBIR) deals with retrieval of relevant images from the large image database. It works on the features of images extracted. In this paper we are using very innovative idea of sectorization of Full Haar Wavelet transformed images for extracting the features into 4, 8, 12 and 16 sectors. The paper proposes two planes to be sectored i.e. Forward plane (Even plane) and backward plane (Odd plane). Similarity measure is also very essential part of CBIR which lets one to find the closeness of the query image with the database images. We have used two similarity measures namely Euclidean distance (ED) and sum of absolute difference (AD). The overall performance of retrieval of the algorithm has been measured by average precision and recall cross over point and LIRS, LSRR. The paper compares the performance of the methods with respect to type of planes, number of sectors, types of similarity measures and values of LIRS and LSRR.
CITED BY (4)  
1 Ghousel, M. K., & Chillakuru, P. (2015). Face Image Retrieval using Contextual and HAAR Feature Extraction. Digital Image Processing, 7(5), 164-166.
2 Kekre, H. B., Mishra, D., Gandhi, V., Deshpande, S., Iyer, R., & Barot, M. (2013). Performance Comparison of DFT and Hartley Plane Sectorization with its Wavelets across RGB, LUV and YCbCr Colour Planes in CBIR. database, 10, 3.
3 Kousalya, S., & Thananmani, A. S. (2013). Image Mining-Similar Image Retrieval Using Multi-Feature Extraction and Content Based Image Retrieval Technique. Image, 2(11).
4 Sulayman, E. N., Ammar, M., & Hossein, J. Analysis study of Content Based Medical Image Retrieval Systems.
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H.B.Kekre, Dhirendra Mishra, “ density distribution in Walsh Transform 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
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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
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 http://www.cscjournals.org/csc/manuscript/Journals/IJIP/Volume4/Issue3/IJIP-193.pdf
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
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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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Professor H.B. Kekre
- India
Associate Professor Dhirendra Mishra
SVKM's NMIMS University - India
dhirendra.mishra@gmail.com


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