Funny I was actually thinking about doing something like this the other day. I will write down what I think is a strategy to do 'intelligent' character recognition. I am quite confident that this technique is able to recognise printed characters in the noisy-ish images generated by sites like PayPal.
Core Component
Multi-layer, back propagating neural network. I will probably use the AI::NeuralNet::BackProp module to do this. The neural-net is then pre-trained with the fonts to be recognised.
Image Processing
You will definitely need to clean up the image somehow before feeding into the character recognition engine. The pre-processing would involve:
color image -> black/white convertion (to simplify the recognition)
noise reduction, including lines that run across the image
a pixel density count, statistics collection, determine text/character boundary
Character Recognition Process
Input is an array of character bitmaps captured by the pre-processing steps
Feed the bitmap into the neural network, and get the best estimate of the character it contains
Output the characters recognised
-
Are you posting in the right place? Check out Where do I post X? to know for sure.
-
Posts may use any of the Perl Monks Approved HTML tags. Currently these include the following:
<code> <a> <b> <big>
<blockquote> <br /> <dd>
<dl> <dt> <em> <font>
<h1> <h2> <h3> <h4>
<h5> <h6> <hr /> <i>
<li> <nbsp> <ol> <p>
<small> <strike> <strong>
<sub> <sup> <table>
<td> <th> <tr> <tt>
<u> <ul>
-
Snippets of code should be wrapped in
<code> tags not
<pre> tags. In fact, <pre>
tags should generally be avoided. If they must
be used, extreme care should be
taken to ensure that their contents do not
have long lines (<70 chars), in order to prevent
horizontal scrolling (and possible janitor
intervention).
-
Want more info? How to link
or How to display code and escape characters
are good places to start.
|