MATLAB provides multiple methods for feature extraction, depending on the task. For general-purpose features, use functions like extractHOGFeatures, extractLBPFeatures, or extractSURFFeatures. These methods capture texture, shape, and key points.
For deep learning-based features, MATLAB’s Deep Learning Toolbox allows you to use pre-trained networks like AlexNet or ResNet. Extract features by passing the image through the network and retrieving outputs from intermediate layers using the activations function.
Preprocess the image before extraction by resizing, normalizing, or converting to grayscale, ensuring compatibility with the chosen feature extraction method.