DocumentCode :
3599142
Title :
Classification Based on Gabor Filter Using RBPNN Classification
Author :
Huang, Zhi-Kai ; Huang, De-Shuang ; Lyu, Michael R. ; Lok, Tat-Ming
Author_Institution :
Hefei Inst. of Intelligent Machines, Chinese Acad. of Sci., Hefei
Volume :
1
fYear :
2006
Firstpage :
759
Lastpage :
762
Abstract :
In this paper, a color pattern recognition technique that is suitable for multicolor images of bark has been analyzed and evaluated. To extract the bark texture features, Gabor filter the image has been filtered with four orientations and six scales filters, and then the mean and standard deviation of the image output are computed. In addition, the obtained Gabor feature vectors are fed up into radial basis function neural network (RBPNN) for classification. The performance of color space features is found to be better than that of the features which just extracted from gray image. The experimental results show this approach can be used to automatically identify the plant categories more effective
Keywords :
Gabor filters; botany; image classification; image colour analysis; image texture; radial basis function networks; Gabor filter; RBPNN classification; bark texture features; color pattern recognition; multicolor images; radial basis function neural network; Filtering; Fractals; Gabor filters; Image analysis; Image color analysis; Image recognition; Image texture analysis; Machine intelligence; Pattern analysis; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Security, 2006 International Conference on
Print_ISBN :
1-4244-0605-6
Electronic_ISBN :
1-4244-0605-6
Type :
conf
DOI :
10.1109/ICCIAS.2006.294237
Filename :
4072190
Link To Document :
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