Title :
Ultra local binary pattern for image texture analysis
Author :
Yiu-ming Cheung ; Junping Deng
Author_Institution :
Dept. of Comput. Sci., Hong Kong Baptist Univ., Hong Kong, China
Abstract :
Local Binary Pattern (LBP) is a simple yet powerful method for image feature extraction in pattern recognition and image processing. However, the LBP operator of each pixel mainly depends on its neighboring pixels and emphasizes on local information too much. From the practical viewpoint, the information is quite limited if we consider the LBP operator in isolation, especially for a large image. To deal with this issue, we propose ultra LBP (U-LBP), which consider the relationship among different LBP operators. The proposed method cannot only get the local but also ultra local information. The effectiveness of the proposed algorithm is investigated on gender recognition and digit recognition, respectively. The experimental results show that the proposed method outperforms the traditional LBP.
Keywords :
feature extraction; gender issues; image texture; object recognition; U-LBP; digit recognition; gender recognition; image feature extraction; image processing; image texture analysis; pattern recognition; ultra LBP; ultra local binary pattern; ultra local information; Databases; Educational institutions; Error analysis; Feature extraction; Gray-scale; Hidden Markov models; Pattern recognition; Co-occurrence Matrix; Feature Extraction; Local Binary Pattern; Ultra Local Binary Pattern;
Conference_Titel :
Security, Pattern Analysis, and Cybernetics (SPAC), 2014 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4799-5352-3
DOI :
10.1109/SPAC.2014.6982701