BTW : Stackoverflow or Quora etc.. would be nice place ask such questions.
There would be more heads to share their experiences and higher chances of
finding a(better) solution(s).

Cheers,
-Sumod


On Mon, Feb 6, 2012 at 9:56 AM, Sumod K Mohan <[email protected]> wrote:

> Hi,
>
> These are my two cents as a Computer Vision/Image processing(Biometrics :
> in the past) researcher.
>
> 1. I do not have a list of softwares for the specific function and am not
> sure if you can find one for "free" (free as in freedom or free beer).
> 2. If you want to built one, here are my suggestions. This is what I would
> do. It might take sometime (say a week or so) to get it working depending
> on your constraints (or accuracy) and your knowledge of the area.
>     a. First and foremost, you will have to create a bounding box of where
> to find the signature.
>     b. Once that is done, the simplest method would be do a simple (sum of
> differences), which is to compare both images locations and see if they
> have same pixel intensities.
>     c. Now get the score for the whole image and anything above a
> threshold would be the right signature and below would not be.
>     d. This will only work, if the signature was exactly the same or very
> very similar and both have the same location inside the bounding box,
> meaning if it is not translated (no lateral movement) and the inter
> character difference is also similar. So the truth is that, it won't work
> most of the time.
>    e. Now a good hack of that would be to do this. I haven't tried this,
> but feel it might be a good experience. You could give this as an input to
> OCR recognition software to detect this as a single character, the
> character being the signature here. Many of the OCR softwares are trained
> in such a way that, it does not care whether the input is translated or
> not. One of the best results are using Yann Lecun's convolutional neural
> networks : http://yann.lecun.com/exdb/lenet/index.html. But even simpler
> ones based on SVM or even a Naive Bayes classifier should work.
>    f. So simply put, the idea is to train the software using sample of
> each persons signature as the character to be recognized. Now during test
> if the match is high, it is good match or else its not.
>
> This is really a very coarse approach, based on 15 min thought.
>
> Regards,
> -Sumod
>
>
>
> On Mon, Feb 6, 2012 at 6:28 AM, Nataraj S Narayan <[email protected]>wrote:
>
>> Hi Srinivas
>>
>> What kind of algorithm does opencv use to compare images? Hand
>> signatures by the same person might never look exactly similar, except
>> that the pattern might be the same.  Hope opencv does more of a
>> pattern analysis.
>>
>> Where can I get some info regarding what goes behind handwriting or
>> signature analysis? Modern banks like Icici might be using some kind
>> of automation for this purpose instead of person checking out on the
>> signature pattern manually?
>>
>> Warm regards
>>
>> Nataraj
>>
>> On Mon, Feb 6, 2012 at 12:46 PM, Shrinivasan T <[email protected]>
>> wrote:
>> > we can use opencv to compare images
>> >
>> > On Feb 6, 2012 12:35 PM, "Nataraj S Narayan" <[email protected]>
>> wrote:
>> >>
>> >> Hi
>> >>
>> >> Anybody aware  of  any Linux based software that compares two
>> >> signature images and
>> >> checks if it is the signature of the same person?
>> >>
>> >> I mean any software that detects forged signatures?
>> >>
>> >> regards
>> >>
>> >> Nataraj
>> >>
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