Let's say I have a small bitmap which contains a single digit (0..9) in hand writing.
Is it possible to detect the digit using a (two-layered) perceptron?
Are there other possibilities to detect single digits from bitmaps besides using neural nets?
Let's say I have a small bitmap which contains a single digit (0..9) in hand writing.
Is it possible to detect the digit using a (two-layered) perceptron?
Are there other possibilities to detect single digits from bitmaps besides using neural nets?
Here is a link to a huge database of handwritten digits. The front page also has relative performance data for many different methods including 2 layer Neural networks. This ought to give you a good start: MNIST digits database and performance
You might also want to check out Geoff Hinton's work on Restricted Boltzmann Machines which he says performs fairly well, and there is a good explanatory lecture on his site (very watchable).
Feeding each pixel of a bitmap directly into a neural network will require a lot of training, and will not work well for handling scaling or rotation of the image.
To help the neural network perform good classification, you need to perform some preprocessing steps.
The principal components can also be used to normalize rotation of the shape, so that the longest axis is vertical.
The features are what you feed into the neural network for classification, not the pixels.
Here is a Matlab example program that uses a trained neural network to detect single digits (image size fixed to 28*28).