Neural network input data, cartesian plane x/y coordinates, correlate with Handwriting

Question

I am very curious about making a handwriting recognition application in a web browser. Users draw a letter, ajax sends the data to the server, the neural network finds the closest match and returns results. So if you draw an ‘a’ the first result should be an a, then o, then e, something like that.

I don't know much about neural networks. What kinda data would I need to pass to the NN. Could it be an array of the x/y coordinates where the user has drawn on a pad? Or what type of data is the neural network expecting or would produce the best results for handwriting?

Answer 1

On-line character recognition is a challenging problem. Much of the difficulty stems from the fact that pattern recognition is a complex process that cannot be solved completely by analytical methods.

Sending the order could cause the NN a lot "smarter", but if you're just learning, try the bitmap version first and see how well it works. Also, play with the bitmap granularity. Possibly you can try digit recognition first, there are standard datasets for that problem on the web. Not only you need to send the X/Y coordinates, but also the ORDER they were drawn in. So a path might be beneficial than just a set of points. A neural net should be able to manage it, and there are many ways it could. One way might be to divide up the path in n segments for n neurons and have each neuron recognize a piece of the letter.

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