Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Digital Object Identifier (DOI) : 10.14569/IJACSA.2011.020212
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 2 Issue 2, 2011.
Abstract: An innovative idea of sectorization of Full Kekre’s Wavelet transformed (KWT) images for extracting the features has been proposed. The paper discusses two planes i.e. Forward plane (Even plane) and backward plane (Odd plane). These two planes are sectored into 4, 8, 12 and 16 sectors. An innovative concept of sum of absolute difference (AD) has been proposed as the similarity measuring parameters and compared with the well known Euclidean distance (ED).The performances of sectorization of two planes into different sector sizes in combination with two similarity measures are checked. Class wise retrieval performance of all sectors with respect to the similarity measures i.e. ED and AD is analyzed by means of its class (randomly chosen 5 images) average precision- recall cross over points, overall average (average of class average) precision-recall cross over points and two new parameters i.e. LIRS and LSRR.
H B Kekre and Dhirendra Mishra, “Sectorization of Full Kekre’s Wavelet Transform for Feature extraction of Color Images ” International Journal of Advanced Computer Science and Applications(IJACSA), 2(2), 2011. http://dx.doi.org/10.14569/IJACSA.2011.020212