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If your time is limited an approach you could try is example based learning. 1) create image vectors from your positive and negative examples 2) feed them to a support vector machine or ANN to make a basic classifier 3) feed a new example and see if it works
This is however very basic. Like many others said, getting to implement something robust can take you some time. This is a large research topic in academic world, with many papers discussig approaches.
Another approach could be to represent your data in a reduced form by applying PCA, but again, it wont be just copy paste of existig codes.
