DocumentCode :
152173
Title :
A novel texture classification method based on Hessian matrix and principal curvatures
Author :
Alpaslan, Nuh ; Hanbay, Kazim ; Hanbay, Davut ; Talu, M. Fatih
Author_Institution :
Bilgisayar Muhendisligi Bolumu, Inonu Univ., Malatya, Turkey
fYear :
2014
fDate :
23-25 April 2014
Firstpage :
160
Lastpage :
163
Abstract :
In this study, in order to obtain similar effect with conventional gradient operation and extract more robust feature for texture, we use the principal curvature informations instead of the gradient calculation. Through this methods, sharp and important informations about the texture images were obtained by analyzing images of the second order. Considering the classification results obtained, it is shown that the proposed method improve the performance of original CoHOG and HOG feature extraction methods. As a result of experiments on datasets with different characteristics, it is seen that, the proposed method has higher classification performance.
Keywords :
feature extraction; image classification; image texture; CoHOG feature extraction methods; HOG feature extraction methods; Hessian matrix; classification performance; principal curvature information; texture classification method; texture feature extraction; texture images; Art; Computer vision; Conferences; Feature extraction; Field programmable gate arrays; Histograms; Signal processing; CoHOG; HOG; Hessian matris; Temel Eğrilikler;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2014 22nd
Conference_Location :
Trabzon
Type :
conf
DOI :
10.1109/SIU.2014.6830190
Filename :
6830190
Link To Document :
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