Authors:
Nitin Arora,Alaknanda Ashok,Shamik Tiwari,DOI NO:
https://doi.org/10.26782/jmcms.2019.08.00046Keywords:
Feature extraction,local binary pattern,texture feature,content based image retrieval,pixel,pixel intensity,Abstract
Local binary patterns (LBP) is a very powerful texture feature of an image. Many variants of LBP models are available and almost all of the derived models are based on the idea to calculate the difference of each central pixel in the 3×3 neighborhood matrix. Based on this difference is positive or negative, we replace neighborhood pixel intensity with 1 or 0 respectively and then convert obtained 0 and 1 pattern into a decimal value. In this paper, we propose modification of this idea, instead of using local binary pattern, local octal and local hexadecimal pattern is used. Local octal pattern (LOP) and the local hexadecimal pattern(LHP) is further tested on two different datasets of 100 images each of sizes 150 x 150 and the obtained results are compared with the state-of-art local binary pattern. For similarity measure, Euclidian distance and Manhattan distance is used. Results show that local octal pattern is superior over local hexadecimal pattern and the local binary pattern is superior over both local octal pattern and local hexadecimal pattern.Refference:
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