How to process extracted SURF features for SVM classifier
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How to process stored surf features of multiple files for svm classifier
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Bilal Razi
il 11 Apr 2020
You can use a combination of functions.
bagOfFeatures and trainImageCategoryClassifier
Use bagOfFeatures to extract your SURF features e.g.
bag = bagOfFeatures(imds, "CustomExtractor", extractorFcn);
where extractorFcn is is a function which extracts your SURF features
then train your model using SVM
classifier = trainImageCategoryClassifier(imds, bag, "LearnerOptions", opts);
where opts = templateSVM()
Hope that helps.
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Divya Gaddipati
il 14 Gen 2020
You can use fitcsvm to train SVM classifier.
You can load the files into the workspace in a loop.
for i = 1 : total_files
x = load(filename(i).name);
XTrain(i,:) = x;
clear x;
end
Assuming your labels are in a variable YTrain, you can use the fitcsvm as follows:
Mdl = fitcsvm(XTrain, YTrain)
For more information on fitcsvm, you can refer to the following link:
Alternatively, you can also use classificationLearner
Hope this helps!
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