Optical character recognition

Question

Hey everyone, I'm trying to create a program in Java that can read numbers of the screen, and also recognise images on the screen. I was wondering how i can achieve this? The font of the numbers will always be the same. I have never programmed anything like this before, but my idea of how it works is to have the program take a screenshot, then overlay the image of the numbers with the section of the screenshot image and check if they match, repeating this for each numbers. If this is the correct way to do this, how would i put that in code.

Thanks in advance for any help.

Answer 1

You could always train a neural net to do it for you. They can get pretty accurate sometimes. If you use something like Matlab it actually has capabilities for that already. Apparently there's a neural network library for java (http://neuroph.sourceforge.net/) although I've never used it personally.

Here's a tutorial about using neuroph: http://www.certpal.com/blogs/2010/04/java-neural-networks-and-neuroph-a-tutorial/

Answer 2

You can use a neural network, support vector machine, or other machine learning construct for this. But it will not do the entire job. If you do a screen shot, you are going to be left with a very large image that you will need to find the individual characters on. You also need to deal with the fact that the camera might not be pointed straight at the text that you want to read. You will likely need to use a series of algorithms to lock onto the right parts of the image and then downsample it in a way that size becomes neutral.

Here is a simple Java applet I wrote that does some of this.

http://www.heatonresearch.com/articles/42/page1.html

It lets you draw on a relatively large area and locks in on your char. Then it recognizes it. I am using the alphabet, but digits should be easier. The complete Java source code is included.

Answer 3

One simpler approach could be to use template matching. If the fonts are same, and/or the size (in pixels)is known, then simple template matching can do the job for you. ifsize of input is unknown, you might have to create copies of images at different scales and do the matching at each scale. One with the extreme value(highest or lowest depending on the method you follow for template matching) is your result. Follow this link for details