Study on image segmentation of rice blast based on support vector machines

The exact image segmentation of rice blast is a key to analyzing and recognizing rice disease automatically.A novel color segmentation algorithm based on Support Vector Machines(SVM) was proposed.The issue of image segmentation is translated into the issue of classification on RGB space.First the disease part pixels and normal part pixels was selected and used to make the train samples.The sample's values of RGB was used to make the characteristic vectors.The SVM was trained by these samples and was tested by other pixels in the image.In order to acquire the best segmentation result,different classification kernel parameters were compared and analyzed.Finally,the color image was segmented with the trained SVM model.The experimental results show that the accuracy based on this SVM model was better than OTSU.