hi,
i am developing English Handwriting OCR. I use Zone based approach for feature extraction. Here I use 64 X 64 images. So i have 64 features for one sample image. My SVM will be Multi-class SVM because i have 52 classes for both capital and simple letters. Here is the format of feature vector.
Class A image1 0:0.222000 1:0.0250222 ..... 63:0.000052 Class A image2 (some float values) .... Class A image400 (some float values)
likewise i have 400 images for both 52 classes. I have read as scaling data increase the accuracy of the prediction. But i have few things to be make clear. 01. Can i use Open CV LibSVM as a Multi-class SVM ? 02. How can i scale these feature values ? 03. Is there any function to get the matching probability of each test feature vector in Open CV LibSVM(i search the Open CV 2.4.5 documentation, but i couldn't find this)
can anyone explain these? , and also with some few code lines if possible.
Thank you