Q:

Is there any code or algorithm for signature recognition?

My users draw their signature in my application using touch events and I convert it to a bitmap. I want to extract unique specifications of each signature and compare it by its specifications stored in main server.
How can I do that?
What is the main and enterprise algorithm for extracting unique features of a signature?
Thanks in advance,

A:

I'm not a computer vision expert, but as a grad student that's dabbled, it sounds like feature exaction is what you're looking for.  The first thing that comes to mind is SIFT (Scale-Invariant Feature Transform).  This algorithm would allow you to compare stored features of an original signature to copies and identify a match with a high level of accuracy, even in the cases that the sample is scaled or rotated.
With a simple Google search you can find a number of scholarly papers, for example this one or this one that are specifically related to using the algorithm for signatures/biometrics.
There is a discussion of using OpenCV with SIFT in this Stack Overflow Article.
If there are better vision algorithms that I'm unaware of that are particularly well suited to this problem I encourage the community to chime in.

A:

Try looking at this resource which uses a neural network to do handwriting recognition. Try looking at this resource too which shows you how to recognize hand written digits. Both projects have full source code.

