如何在OpenCV和C ++中配置CvSVM进行图像分类 [英] How to configure CvSVM for image classification in OpenCV and C++

问题描述

我正在开发一个使用OpenCV LibSVM的手写字符识别系统。我已经为特征向量提取了14个特征，包括Hu矩，仿射不变矩，角数等。对于每个角色，我使用5个样本（对于字母A，有5种类型的A'）。我知道5个样本是不够的，但是在那时我每个角色只有5个样本。



我在opencv文档中使用了基本的LINEAR SVM示例。我的问题是，为了我的目的，我可以使用该文档示例吗？我读过有关使用多类SVM的OCR系统。我是否需要这种多类SVM用于我的应用程序。我不明白这一点。请有人解释一下吗？这是我的代码。

i am developing a handwritten character recognition system using OpenCV LibSVM. i have extracted 14 features for the feature vector including Hu moments, affine invariant moments, numbers of corners etc. For each character, i use 5 samples( for letter "A", there 5 types of A''s). I know 5 samples is not enough, but at the moments i have only 5 samples for each character.

I use the basic LINEAR SVM example in opencv documentation. My problem is, can i use that documentation example as it is, for my purpose. I have read about OCR systems that use multi- class SVMs. Do i need such Multi-Class SVM for my application. I do not understand about this. Please can someone explain ? Here is my code.

float labels[180][1] = {1.0, 2.0, 3.0, 4.0, 5.0, ,,,,, -> 180.0};
Mat matlabesls(180,1, CV_32FC1, labels);


Mat mattrainingDataMat(180, 14, CV_32FC1, ifarr_readtrainingdata);

CvSVMParams params;
params.svm_type    = CvSVM::C_SVC;
params.kernel_type = CvSVM::LINEAR;
params.term_crit   = cvTermCriteria(CV_TERMCRIT_ITER, 100, 1e-6);

CvSVM SVM;
SVM.train(mattrainingDataMat,matlabesls,Mat(),Mat(),params);

Mat matinput(1,14,CV_32FC1,ifarr_testarray);
is_recognizedcharacter= SVM.predict(matinput);

return is_recognizedcharacter;

推荐答案

你应该联系OpenCV LibSVM的人。社区。



http://docs.opencv.org/index .html＃ [ ^ ]



有Q& A论坛和一些教程 - 所以你需要继续

you should contact someone from the OpenCV LibSVM. community.

http://docs.opencv.org/index.html#[^]

There is the Q&A Forum and some tutorials - so all you should need to "go ahead"

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