I am trying to detect specific objects in images using Haar cascade in OpenCV.

Let's say I am interested in detecting stop signs in landscape images. When defining positive image samples for my training set, which would be the best kind of image: (a) full images with my object, (b) a medium crop or (c) a tight crop?

[![stop sign](https://i.stack.imgur.com/P61Gr.jpg)](https://i.stack.imgur.com/P61Gr.jpg)

Similarly, what's best for negative images? Does this influence overfitting? I would also appreciate any other general tips from those with experience. Thanks.

Image ref: <http://kaitou-ace.deviantart.com/art/Stop-sign-on-a-country-road-Michigan-271990933>