Hi I am a beginner and totally new for opencv and I wish to ask that whether the SVM classifier in opencv can use for digital signal processing?because so far the tutorial provided is for image processing only and I plan to use and learn opencv for digital signal classification. Please reply me as soon as possible and thank you :)
Well, SVM is a machine learning technique that is not specific to vision applications. Having said that, SVM may well be used for DSP applications (and plenty of others). The implementation in OpenCV is not specific to images, but requires the data being formatted as Mat structures, which makes possible the use of the algorithm for other applications too. In other words, your data (are they features extracted from signals? what's their numerical type? what's their dimensionality?) must follow the Mat format for using the OpenCV implementation of SVM. This is the only requirement.
Thanks a lot for the explanation regarding my question. What if my signal data is in sampling rate?Can it follow the Mat format for using OpenCV implementation of SVM?And how to write it into Mat format? Please reply me as soon as possible and thank you again for the help :)
Well this has to do with the speed of your computer. Why don't you try a simulation experiment? That is, create a bunch of Mat structures with the number and size that you want, and measure how long it takes to create/process them with openCV. In this link (http://docs.opencv.org/doc/tutorials/ml/introduction_to_svm/introduction_to_svm.html) you can find a nice tutorial on how to feed the Mat structure with training data, etc.
Asked: 2013-10-20 15:38:13 -0600
Seen: 332 times
Last updated: Oct 20 '13
