I don't know if this is the right place to ask this but lets go. I am a beginner in computer vision and I have a project of fruit recognition based on Kaggle's Fruit 360 dataset. I know that CNNs are the obvious choice but I wanted to try some classical approaches (and practice OpenCV in the process :) ). But I don't know what would be good methodological choices. I thought about using Histogram of Oriented Gradients, Global Color Histogram, but I am not sure if they are relevant. Also, would PCA make sense here? I would be thankful for any ideas.