图像的哪些特征将产生用于SVM多类图像分类的良好结果？

Question

我正在使用opencv2.4和python 2.7。图像的哪些功能可以用于svm分类。我经历了冲浪和筛选，但作为一个初学者，对我来说似乎很难。其他特征提取技术是什么？

Answer 1

If you are looking for simplest representation then this will help you.These two are very simple compared to other SIFT and SURF

1. Bitmap representation
2. HOG-Histogram of Gradients

SVM is a machine learning model for data classification.I have built a simple svm classifier.If you have two folder of images,birds and squireels.The steps i followed are

1. Extracted Hog features of Images and append that in a list

    for file in listing1: img = cv2.imread(path1 + file) res=cv2.resize(img,(250,250)) h=hog(res) training_set.append(h) 

2. append the labels also

     training_labels.append(1) 

3. convert both lists to numpy array.

    trainData=np.float32(training_set) responses=np.float32(training_labels) 

4. Train SVM

    svm.train(trainData,responses, params=svm_params) 

5. Test SVM

    result = svm.predict_all(testData) print result