Classification based on gabor filter using RBPNN classification
Refereed conference paper presented and published in conference proceedings

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AbstractIn 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. © 2006 IEEE.
All Author(s) ListHuang Z.-K., Lyu M.R., Huang D.-S., Lok T.-M.
Name of Conference2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
Start Date of Conference03/10/2006
End Date of Conference06/10/2006
Place of ConferenceGuangzhou
Country/Region of ConferenceChina
Detailed descriptionorganized by IEEE,\n\nTo ORKTS: available at IEEE Xplore
Volume Number1
Pages759 - 762
LanguagesEnglish-United Kingdom

Last updated on 2020-05-07 at 02:11