OCR in java

hi all,
i want to develop a code for Optical Character Recognition in java. The software should be able to read both handwritten and printed documents. i need to provide options for various formatting also..
I dont know where to start..
can anybody help???
Thanks in advance...

Regards,
Sunitha.

Quote:

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Originally Posted by sunithamm

hi all,
i want to develop a code for Optical Character Recognition in java. The software should be able to read both handwritten and printed documents. i need to provide options for various formatting also..

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Implementing a (more or less) functional OCR system cannot be done in a week or so; it's complicated matter and the existing systems apply two different (sub)systems for hand written and printed text. The two just don't work well together.

Some form of neural network is used in most of the existing systems. Google for 'BAM' (Bidirectional Associative Memory); it's a neural net suitable for image recognition. You can also try to download an existing (free) OCR system; there are a couple of them floating around on the net.

kind regards,

Jos

;-)

Well, although its not a java specific topic (besides the use of java language) i want to provide some suggestions.

I hope its for your study otherwise stop reading and usesome third party tools.
:p

Like Jos said a system for OCR has usually two parts (besides the handwritten and computerwritten chars). And is not realizable under one week or so.

If your system is based on statistical learning then the first part is the "learning" engine (see Supvervised Learning in AI).
The second one is the real AI which do the actual work.

You asked where to start. Start with the first Part!
1. Before you begin the development provide data for training and test! (usually a set of OCs data is free of charge at the universities)
2. Provide methods for Data Input/Import
3. Now create your AI: There are several approaches (read Articles provided by many reasearchers! -> google scholar is your friend)

To name a few which come to my mind first:

1. Using Genetic Algorithms (GA)
   
   • Especially Evolutionary Algorithms
2. Using Neural Nets
   
   • Backpropagation Network
   • Selforganizing Maps (very promising)
   • Radial basis Functions
3. Normalized Compression Distance + SVM

Of course SVM can also be applied in some way, but for now i dont know how ;-) (svmlight is a nice library)

4. Now train and test your AI

When the training is done, extract parameters and configuration and transfer them to the final application, test the application for real acquired data and you're done ;-)

Sound easy, hm ?

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Originally Posted by AndreB

Sound easy, hm ?

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Wow, this stuff really is advanced. :D I'm going to do my honors next year and it includes "Genetic Algorithms". Not sure if it includes "Neural Nets". Sounds awesome though. ;) Sorry for the off topic post.

Tim

Have a look at GOCR

(it wont let me post a link, google GOCR)

It's a functional open source char recognition program. You could read the source code and get an idea of how it is achieved.

thanks a lot for al the help
i am using PixelGrabber class to convert an image into array of pixels. A document image contains so many letters. can anybody tell me hw to get individual letters??
Thanks in advance..

Regards,
Sunitha.