Re: easy way to recognize handwritten character

hi friend,

I understand your concern that it may not work for characters, but
just run the code I have given you and absorb, you will realize that
it is easy to recognize the characters also.

We had a mechanism to break up complex characters into simple ones
(based on the intersection of pixels) and its even easier to recognize
complex characters that way because you have a high probability of
same parts occuring.

I can mail you that paper which says how to split characters into
simple ones and a simple rule based system works. A character can be
viewed as a set of simple digits when broken down at the intersection
of point of two pixels. How to do it, if you want that algorithm, I
can explain.

I cannot paste that paper because it has diagrams and you need those
diagrams to understand that simple logic.

I can mail that if you want.

bye,
RAMESH

"Jean-Baptiste Hétier" <[EMAIL PROTECTED]> wrote in message news:<[EMAIL PROTECTED]>...
> If I understood your idea, I don't think it will work for **handwritten**
> charaters !
> A quite easy way which I have tries myself is to use neural networks (with
> any program you can find on the net). Then just try different networks and
> train them properly (with huge databases). I managed to recognise 93% of
> another database then (and I am sure it is easy to do much better !)
> 
> 
> "RAMESH" <[EMAIL PROTECTED]> a écrit dans le message de
> news:[EMAIL PROTECTED]
> > hi friends,
> >
> > It's easy to recognize a handwritten character recognition easily
> > without applying complex theorems at all.
> >
> > the idea is to not to recognize the character as an image , just think
> > of a blind man how he tries the recognize a character. There lies the
> > logic.
> >
> > Just move over the character recursively in all direction, when you
> > move over it try to recgonize wheather you are in which direction.
> > Then a simple if else rule structure, where you write if I move first
> > horizontal, then vertical , then horizontal , then vertical and then
> > horizontal , then it may be zero or six.
> >
> > Here also you can distinguish from zero and six by using divide and
> > conquer rule , if it six then the first half will be different from
> > second half.
> >
> > for characters, it is more simple rules instead of saying horizontal
> > and vertical , just say  he moves first in 65 degrees in down, then at
> > 20 vertical like that.
> >
> > Even little more or rule struecture can further improve the structure
> > of recognition. like characterzing the distance moved in long, medium
> > , and small.
> >
> > ex. like writing a rule that he moved a long distance from this point
> > and then small distance from here, so we can remove the significance
> > of small if needed. But only problem is there the set of rule is
> > little bit more like nearly more than 100.
> >
> > For discontinutity also there was a solution, to first recongize the
> > disconnect part and say if first half is some what like this and
> > second half is like this it may be this character.But here we tried to
> > joing all the disconnected parts if it dint match to any character and
> > then try out the permutations of it to match with the existing
> > character.
> >
> > It's really easy. It does not take more than 500 lines of code to
> > write because first part you are writing a recursive algorithm.
> >
> > RAMESH
> > for any queries or help, you can contact me at
> > [EMAIL PROTECTED]