Error Concealment | JPEG | MPEG-4 | Wavelet | YUV

dear all members
I am trying to find rate of difference or rate of similarity of two
Images.
anyone can give me any Idea ?
for example :
if we have 2 Image : im1.jpg and im2.jpg
----------------------------------
f1=imread('im1.jpg');
f2=imread('im2.jpg');
F1=fft2(f1);
F2=ff2(f2);
similarity(f1,f2)=?
-------------------------------
How can I compare this two Fouriers?
How can I find rate of similarity of this two image?
the expected results are something like this:
similarity(f1,f2)=99.9
similarity(f1,f3)=98.7
similarity(f1,f4)=34.5
....
Thanks

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perhaps you may try image subtraction of image difference operations...if
t=
he images are of the same size then these image calculations=A0 may determi=
ne the diferences you are after...hope this helps
cheers

--- On Thu, 7/1/10, mohammad <m...@yahoo.com> wrote:
From: mohammad <m...@yahoo.com>
Subject: [imagedsp] How to detection similarity of two Image
To: i...@yahoogroups.com
Received: Thursday, 7 January, 2010, 5:44 AM
dear all members
I am trying to find rate of difference or rate of similarity of two
Images.
anyone can give me any Idea ?
for example :
if we have 2 Image : im1.jpg and im2.jpg
----------------------------------
f1=3Dimread('im1.jpg');
f2=3Dimread('im2.jpg');
F1=3Dfft2(f1);
F2=3Dff2(f2);
similarity(f1,f2)=3D?
-------------------------------
How can I compare this two Fouriers?
How can I find rate of similarity of this two image?
the expected results are something like this:
similarity(f1,f2)=3D99.9
similarity(f1,f3)=3D98.7
similarity(f1,f4)=3D34.5
....
Thanks=20

_____________________________________

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You can also compute the correlation between these two images and look for
the picks; the same which we apply in template matchings and so forth. 

bests

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Hello mr. mohammad
for similarity evaluation
you can calculate the corrolation coeficient of two images
using this command: corr2(f1,f2)
this will give you anumber in the interval of [0 1]
1 shows full similarity and 0 shows no similarity.
you also can comper the histogram of images
or simply the squar error between to images as :
Error=sum(sum((f1-f2).^2))

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Dear, Mehrnaz
Thanks for ur Idea.
I tried both of the your seggustion ( Corr2( ) , and Sum(sum( )).
but these method do the similarity estimation with pixel-by-pixel. and they are
not robust against a bit modification .
I need an effective Discriminative Invariant Features of Image that be robust
against small modification for example rotation.
Thanks again , 
plz Give me your Idea , If you have another one. 
In my opinion , there is need to robust feature in frequency domain !
for example if we have 3 blocks: 
A1= 
248     253     251     253 
245     252     250     253 
245     252     251     254 
248     252     252     254 

A2= 
252     252     251     251 
252     252     251     251 
252     252     252     252 
253     252     252     252 

D1= 
229     229     229     229 
229     229     229     229 
229     0         229     229 
229     229     229     229 

D2= 
1        200       3      0 
80      2          30     50 
100    50        200   90 
0        2          70     1 

we have to be able to find percentage of similarity of these blocks. 
in this example - 
the result has to be  something like these: 
1- similarity(A1,A2)   -----> 99.99% 
2- similarity(A1,D1)   ----->  80% 
3- similarity( A1,D2) --------> 10% 
 
Best Regards

Mohammad Akbarpour Sekeh
Student of PhD in Computer Forensic -IFD area
Faculty of Computer Science and Information system
University Technology Malaysia
81310 UTM Skudai, Johor, Malaysia
Cell-Phone:+60-127890645

________________________________
From: mehrnaz fani <f...@gmail.com>
To: mohammad <m...@yahoo.com>
Cc: i...@yahoogroups.com
Sent: Fri, 8 January, 2010 14:12:51
Subject: Re: [imagedsp] How to detection similarity of two Image
Hello mr. mohammad
for similarity evaluation
you can calculate the corrolation coeficient of two images
using this command: corr2(f1,f2)
this will give you anumber in the interval of [0 1]
1 shows full similarity and 0 shows no similarity.
you also can comper the histogram of images 
or simply the squar error between to images as :
Error=sum(sum((f1-f2).^2))
      

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(You need to be a member of imagedsp -- send a blank email to imagedsp-subscribe@yahoogroups.com )

Try xcorr2(), then=E2=80=A6 It gives a peak at a location depending on the
=
amount of a shifting perturbation. If you have rotative or scaling perturba=
tions, then you may try multi resolution approaches together with KLT (for =
alignment). If you have scaling or rotation, so does the frequency domain. =
Please let us know if you find a robust feature there.

=20

Best,

=20

Omer

=20

From: i...@yahoogroups.com [mailto:i...@yahoogroups.com] On Behalf =
Of mohammad akbarpour
Sent: Friday, January 08, 2010 9:30 AM
To: mehrnaz fani
Cc: i...@yahoogroups.com
Subject: Re: [imagedsp] How to detection similarity of two Image

=20

Dear, Mehrnaz
Thanks for ur Idea.
I tried both of the your seggustion ( Corr2( ) , and Sum(sum( )).
but these method do the similarity estimation with pixel-by-pixel. and they=
 are not robust against a bit modification .
I need an effective Discriminative Invariant Features of Image that be robu=
st against small modification for example rotation.
Thanks again ,=20
plz Give me your Idea , If you have another one.=20
In my opinion , there is need to robust feature in frequency domain !
for example if we have 3 blocks:=20
A1=3D=20
248     253     251     253=20
245     252     250     253=20
245     252     251     254=20
248     252     252     254=20

A2=3D=20
252     252     251     251=20
252     252     251     251=20
252     252     252     252=20
253     252     252     252=20

D1=3D=20
229     229     229     229=20
229     229     229     229=20
229     0         229     229=20
229     229     229     229=20

D2=3D=20
1        200       3      0=20
80      2          30     50=20
100    50        200   90=20
0        2          70     1=20

we have to be able to find percentage of similarity of these blocks.=20
in this example -=20
the result has to be  something like these:=20
1- similarity(A1,A2)   -----> 99.99%=20
2- similarity(A1,D1)   ----->  80%=20
3- similarity( A1,D2) --------> 10%=20

=20
Best Regards

Mohammad Akbarpour Sekeh
Student of PhD in Computer Forensic -IFD area
Faculty of Computer Science and Information system
University Technology Malaysia
81310 UTM Skudai, Johor, Malaysia
Cell-Phone:+60-127890645

=20

=20

  _____=20=20

From: mehrnaz fani <f...@gmail.com>
To: mohammad <m...@yahoo.com>
Cc: i...@yahoogroups.com
Sent: Fri, 8 January, 2010 14:12:51
Subject: Re: [imagedsp] How to detection similarity of two Image

Hello mr. mohammad

for similarity evaluation

you can calculate the corrolation coeficient of two images

using this command: corr2(f1,f2)

this will give you anumber in the interval of [0 1]

1 shows full similarity and 0 shows no similarity.

you also can comper the histogram of images=20

or simply the squar error between to images as :

Error=3Dsum(sum((f1-f2).^2))

_____________________________________

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(You need to be a member of imagedsp -- send a blank email to imagedsp-subscribe@yahoogroups.com )

Dear All,

Hello and Happy new year!

For comapring two images or signals and for measuring rthe similarities, on=
e of the=C2=A0approaches is to extract features and then, compare these fea=
tures. As=C2=A0you mentioned these features are suppoosed to be invariant=
=C2=A0with respect to tranlation, rotation, and scale. For example co-occur=
rence matrix=C2=A0feature extraction method and Hu moments are widely used =
for image analysis and classification. However, selecting the aproach reall=
y depends on the application. You can find more about them in image process=
ing and pattern recognition text books.

I hope this would be helpful.

Best regards,
Alireza
=C2=A0

________________________________
From: mohammad akbarpour <m...@yahoo.com>
To: mehrnaz fani <f...@gmail.com>
Cc: i...@yahoogroups.com
Sent: Fri, January 8, 2010 8:30:29 AM
Subject: Re: [imagedsp] How to detection similarity of two Image

=C2=A0=20
Dear, Mehrnaz
Thanks for ur Idea.
I tried both of the your seggustion ( Corr2( ) , and Sum(sum( )).
but these method do the similarity estimation with pixel-by-pixel. and they=
 are not robust against a bit modification .
I need an effective Discriminative Invariant Features of Image that be robu=
st against small modification for example rotation.
Thanks again ,=20
plz Give me your Idea , If you have another one.=20
In my opinion , there is need to robust feature in frequency domain !
for example if we have 3 blocks:=20
A1=3D=20
248 =C2=A0 =C2=A0 253 =C2=A0 =C2=A0 251 =C2=A0 =C2=A0 253=20
245 =C2=A0 =C2=A0 252 =C2=A0 =C2=A0 250 =C2=A0 =C2=A0 253=20
245 =C2=A0 =C2=A0 252 =C2=A0 =C2=A0 251 =C2=A0 =C2=A0 254=20
248 =C2=A0 =C2=A0 252 =C2=A0 =C2=A0 252 =C2=A0 =C2=A0 254=20

A2=3D=20
252 =C2=A0 =C2=A0 252 =C2=A0 =C2=A0 251 =C2=A0 =C2=A0 251=20
252 =C2=A0 =C2=A0 252 =C2=A0 =C2=A0 251 =C2=A0 =C2=A0 251=20
252 =C2=A0 =C2=A0 252 =C2=A0 =C2=A0 252 =C2=A0 =C2=A0 252=20
253 =C2=A0 =C2=A0 252 =C2=A0 =C2=A0 252 =C2=A0 =C2=A0 252=20

D1=3D=20
229 =C2=A0 =C2=A0 229 =C2=A0 =C2=A0 229 =C2=A0 =C2=A0 229=20
229 =C2=A0 =C2=A0 229 =C2=A0 =C2=A0 229 =C2=A0 =C2=A0 229=20
229 =C2=A0 =C2=A0 0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 229 =C2=A0 =C2=A0 229=20
229 =C2=A0 =C2=A0 229 =C2=A0 =C2=A0 229 =C2=A0 =C2=A0 229=20

D2=3D=20
1 =C2=A0 =C2=A0 =C2=A0=C2=A0 200 =C2=A0 =C2=A0 =C2=A0 3 =C2=A0 =C2=A0 =C2=
=A00=20
80 =C2=A0 =C2=A0 =C2=A02 =C2=A0 =C2=A0 =C2=A0 =C2=A0=C2=A0 30 =C2=A0 =C2=A0=
 50=20
100 =C2=A0=C2=A0 50 =C2=A0 =C2=A0=C2=A0 =C2=A0 200=C2=A0=C2=A0 90=20
0 =C2=A0 =C2=A0 =C2=A0=C2=A0 2 =C2=A0 =C2=A0=C2=A0 =C2=A0 =C2=A0 70 =C2=A0 =
=C2=A0 1=20
we have to be able to find percentage of similarity of these blocks.=20
in this example -=20
the result has to be=C2=A0 something like these:=20
1- similarity(A1, A2) =C2=A0 -----> 99.99%=20
2- similarity(A1, D1) =C2=A0 -----> =C2=A080%=20
3- similarity( A1,D2) --------> 10%=20

Best Regards

Mohammad Akbarpour Sekeh
Student of PhD in Computer Forensic -IFD area
Faculty of Computer Science and Information system
University Technology Malaysia
81310 UTM Skudai, Johor, Malaysia
Cell-Phone:+ 60-127890645=20

________________________________
From: mehrnaz fani <fani.mehrnaz@ gmail.com>
To: mohammad <moh_akb_s@yahoo. com>
Cc: imagedsp@yahoogroup s.com
Sent: Fri, 8 January, 2010 14:12:51
Subject: Re: [imagedsp] How to detection similarity of two Image
Hello mr. mohammad
for similarity evaluation
you can calculate the corrolation coeficient of two images
using this command: corr2(f1,f2)
this will give you anumber=C2=A0in the interval of=C2=A0[0 1]
1 shows full similarity and 0 shows no similarity.
you also=C2=A0can comper the histogram of images=20
or simply=C2=A0the=C2=A0squar error between to images as :
Error=3Dsum(sum( (f1-f2).^ 2))

=20=20=20=20=20=20

_____________________________________

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Hi
For measuring similarity of two image you have to use image siedility metrics
such as MSE,PSNR,SSIM,NC,...
Regards

dear all members
>I am trying to find rate of difference or rate of similarity of two
>Images.
>anyone can give me any Idea ?
>for example :
>if we have 2 Image : im1.jpg and im2.jpg
>----------------------------------
>f1=imread('im1.jpg');
>f2=imread('im2.jpg');
>F1=fft2(f1);
>F2=ff2(f2);
>similarity(f1,f2)=?
>-------------------------------
>How can I compare this two Fouriers?
>How can I find rate of similarity of this two image?
>the expected results are something like this:
>similarity(f1,f2)=99.9
>similarity(f1,f3)=98.7
>similarity(f1,f4)=34.5
>....
>Thanks

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> try this paper and find more in its reference section. 
> http://www.cs.uwa.edu.au/~gian/docs/hons_paper.pdf

Here is updated URL:

http://www.csse.uwa.edu.au/~pk/studentprojects/gian/hons_paper.pdf

Best regards,
Mateusz Loskot

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