What are good counter-examples when training an apple classifier? I am doing a project in order to recognize an apple. (I am using Emgucv with Visual Studio 2010 C#, if that's relevant). My project is a classification (is or is not an apple). I have 2000 images of apples but I need images for the second class. 

I have read about classification using ANN but they have multiple classes but I need to recognize if image contain an apple or not. So what kind of images do I need for the second classes? I want to use background of apples like second class. Is that a good idea?

I only want that ANN recognize if a image contain a pen or not so I have 2 classes(pen and non-pen) My question is What kind of image can I use to the second class? For example My first class are images of pen and second class are images of non pen (pencil, apples, grapes, tables); is that correct?
A standard approach is to pick a standard image bank of other images that you might run into that aren't apples, and use that as your other class.  The way you figure out what kind of images you need is: figure out what kind of images your classifier might be run on, and try to make the training set as similar as possible to the kinds of images that it will be run on in production.