How to classify the image using SVM training with trainset?

image classification using image features extraction from the new image and using SVM to train and compare the new image features with the trainsets features at the end print the result.

Answer 1

[Harsh]

Hi Rohullah,

Feature extraction is an important step in machine learning that involves transforming raw data into a set of numerical features that can be used for modeling. To understand more about feature extraction, please refer to the following page - https://www.mathworks.com/discovery/feature-extraction.html .

You can extract the local binary pattern (LBP) features or the histogram of oriented gradients (HOG) features using the “extractLBPFeatures” and “extractHOGFeatures” functions respectively. Please run the following commands in command line to open documentation for these functions –

doc extractLBPFeatures  
doc extractHOGFeatures  

“fitcsvm” function can be used for training support vector machine (SVM) classifier for one-class and binary classification. To open the documentation for “fitcsvm” function, please enter the following command in command line

doc fitcsvm 

Please refer to the following page for more information regarding the SVM Classification - https://www.mathworks.com/help/stats/support-vector-machine-classification.html

Use the “predict” function to get the result using SVM model. Please refer to the following page for more information regarding the “predict” function

doc predict