This is a toy example of the kind of problem that the field of Computer Vision is actively working on: object detection. In a (tiny) nutshell, our best answer for general images and objects is:
1) Instead of using the full color pixel image, use an "edge image" with some simple additional normalizations. If color is important, do this per color channel.
2) Create a dataset with as many cropped examples of the target object as you can find (mechanical turk is useful for annotating large datasets); every other crop of every image is a negative example.
3) Train a classifier (SVM if you want it to work, neural network if you're so inclined) using this dataset.
4) Apply the classifier to all subwindows of a new image to generate hypotheses of the target object location. This can be sped up in various ways, but this is the basic idea.
5) Post-process the hypotheses using context (can be as simple as simply finding the most confident hypotheses within a neighborhood).
If you're interested in object detection, an excellent recent summary of the recent decade of research is due to Kristen Grauman and Bastian Leibe: http://www.morganclaypool.com/doi/abs/10.2200/S00332ED1V01Y2... (do some googling if you don't have access to this particular PDF).
1) Instead of using the full color pixel image, use an "edge image" with some simple additional normalizations. If color is important, do this per color channel.
2) Create a dataset with as many cropped examples of the target object as you can find (mechanical turk is useful for annotating large datasets); every other crop of every image is a negative example.
3) Train a classifier (SVM if you want it to work, neural network if you're so inclined) using this dataset.
4) Apply the classifier to all subwindows of a new image to generate hypotheses of the target object location. This can be sped up in various ways, but this is the basic idea.
5) Post-process the hypotheses using context (can be as simple as simply finding the most confident hypotheses within a neighborhood).
If you're interested in object detection, an excellent recent summary of the recent decade of research is due to Kristen Grauman and Bastian Leibe: http://www.morganclaypool.com/doi/abs/10.2200/S00332ED1V01Y2... (do some googling if you don't have access to this particular PDF).
A cool paper from a few months ago that should be mentioned when commenting on a post called "Where's Waldo?" is http://www.cs.washington.edu/homes/rahul/data/WheresWaldo.ht...