General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • E-mail: ijcte@iacsitp.com
    • Journal Metrics:

Editor-in-chief
Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2011 Vol.3(2): 217-223 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2011.V3.308

Sectorization of Full Walsh Transform for Feature Vector Generation in CBIR

H. B. Kekre and Dhirendra Mishra

Abstract—We have introduced a novel idea of sectorization of complex Full Walsh transformed components. In this paper we have proposed two different approaches along with augmentation of mean of zero and highest row components of row transformed values and mean of zero- and highest column components of Column transformed values for feature vector generation namely SS-CC Plane and SC-CS Plane. We have introduced the new performance evaluation parameters i.e. LIRS and LSRR apart from precision and Recall, the traditional methods. Two similarity measures such as sum of absolute difference and Euclidean distance are used and results are compared. The cross over point performance of overall average of precision and recall for both approaches on different sector sizes are compared. The Full walsh transform sectorization is experimented on both SS-CC and SC-CS Plane with augmentation and without augmentation for the color images. The algorithm proposed here is worked over database of 1055 images spread over 12 different classes. Overall Average precision and recall is calculated for the performance evaluation and comparison of 4, 8, 12 & 16 Full Walsh sectors. The use of Absolute difference as similarity measure always gives lesser computational complexity and density distribution approach with sum of absolute difference as similarity measure of feature vector has the best retrieval performance.

Index Terms—CBIR, Walsh Transform, Euclidian Distance, Absolute Difference, Precision, Recall

Dr. H. B. Kekre is senior professor with the Mukesh Patel School of Technology Management and Engineering, SVKM’s NMIMS University, Vile Parle Mumbai-56 INDIA. Phone: +919323557897; e-mail: mailto:hbkekre@yahoo.com
Dhirendra Mishra is Associate Professor and PhD Research Scholar with the Mukesh Patel School of Technology Management and Engineering, SVKM’s NMIMS University, Vile Parle Mumbai-56 INDIA. Phone: +919867676425; e-mail: mailto:dhirendra.mishra@gmail.com

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Cite: H. B. Kekre and Dhirendra Mishra, "Sectorization of Full Walsh Transform for Feature Vector Generation in CBIR," International Journal of Computer Theory and Engineering vol. 3, no. 2, pp. 217-223, 2011.


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