Classification Based on Gabor Filter Using RBPNN Classification

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