D
dede
Dear all,
in order to provide a convenient method for photographer like me to
detect "equal" or "similar" pictures I am trying to develop a perl
function/method that does exactly this:
Input: JPG file
Output: MD5-like fingerprint of JPG (to be stored in a db)
It should be a hash-value that is very close if two pics are "almost
identical". It must be robust against at least JPG-rotations
(90/180/270 degrees) and "reasonable" scalings. The analysis will be
stored in the EXIF-data of the JPG so the analysed data should be only
the "naked JPG-data" itself.
My basic idea is to create a 2-dimensional bitmap that will be
"normalized", i.e. rotated to a "zero-position" and scaled to let's
say a 1000x1000 JPG.
"Sugar" for this algorithm could be robustness against primitiv
operations like flipping, clipping, changing contrast, watermarking,
etc.
Is there anyone in the community who has done this already? Any help
will be appreciated.
Thanx in advance. Merci.
Andreas
in order to provide a convenient method for photographer like me to
detect "equal" or "similar" pictures I am trying to develop a perl
function/method that does exactly this:
Input: JPG file
Output: MD5-like fingerprint of JPG (to be stored in a db)
It should be a hash-value that is very close if two pics are "almost
identical". It must be robust against at least JPG-rotations
(90/180/270 degrees) and "reasonable" scalings. The analysis will be
stored in the EXIF-data of the JPG so the analysed data should be only
the "naked JPG-data" itself.
My basic idea is to create a 2-dimensional bitmap that will be
"normalized", i.e. rotated to a "zero-position" and scaled to let's
say a 1000x1000 JPG.
"Sugar" for this algorithm could be robustness against primitiv
operations like flipping, clipping, changing contrast, watermarking,
etc.
Is there anyone in the community who has done this already? Any help
will be appreciated.
Thanx in advance. Merci.
Andreas