[Insight-users] Image Symilarity Metrics suggestion
Miller, James V (Research)
millerjv@crd.ge.com
Wed, 22 Jan 2003 12:14:32 -0500
This message is in MIME format. Since your mail reader does not understand
this format, some or all of this message may not be legible.
------_=_NextPart_000_01C2C239.6BED5ACA
Content-Type: multipart/alternative;
boundary="----_=_NextPart_001_01C2C239.6BED5ACA"
------_=_NextPart_001_01C2C239.6BED5ACA
Content-Type: text/plain;
charset="iso-8859-1"
You can use the itk::ImportImageFilter to interface an existing image source to ITK. You pass this
filter a pointer to the block of memory containing the pixel data and tell the filter the appropriate
size (and data type). The output of this filter can then be passed to the various image metrics.
Jim
-----Original Message-----
From: Fabio Interlenghi [mailto:f.interlenghi@diapasonsrl.it]
Sent: Wednesday, January 22, 2003 11:27 AM
To: insight-users@public.kitware.com
Subject: [Insight-users] Image Symilarity Metrics suggestion
Hi All,
I'm novice in ITK programming and trying to understand the best way to do Image comparison.
The objective is to build a keyframe grabbing for video contents and the problem to solve for me is
to compare two images and then get a measurement of the difference between them.
The analysis will be done between two images in memory and not read from a file so in which way can
i convert a DIB image in to itk::Image?
Can you help me indicating a tutorial or an example or what ever you think could help?
Many thanks in advance.
Regards.
Fabio Interlenghi
Direzione Tecnica
Media Businness Unit
http://www.diapasonsrl.it <http://www.diapasonsrl.it/>
Via Torre Pellice, 17
10156 Torino
Tel.: 0112743095
Fax : 0112735640
Mob.: 3357887348
------_=_NextPart_001_01C2C239.6BED5ACA
Content-Type: text/html;
charset="iso-8859-1"
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN">
<HTML><HEAD>
<META HTTP-EQUIV="Content-Type" CONTENT="text/html; charset=iso-8859-1">
<META content="MSHTML 6.00.2715.400" name=GENERATOR></HEAD>
<BODY>
<DIV><SPAN class=716021217-22012003><FONT color=#0000ff size=2>You can use the
itk::ImportImageFilter to interface an existing image source to ITK. You
pass this filter a pointer to the block of memory containing the pixel data and
tell the filter the appropriate size (and data type). The output of this
filter can then be passed to the various image metrics.</FONT></SPAN></DIV>
<DIV><SPAN class=716021217-22012003><FONT color=#0000ff
size=2></FONT></SPAN> </DIV>
<DIV><SPAN class=716021217-22012003><FONT color=#0000ff
size=2>Jim</FONT></SPAN></DIV><SPAN class=716021217-22012003></SPAN><FONT
face=Tahoma>
<DIV><BR> </DIV>
<DIV><FONT size=2><SPAN class=716021217-22012003> </SPAN>-----Original
Message-----<BR><B>From:</B> Fabio Interlenghi
[mailto:f.interlenghi@diapasonsrl.it]<BR><B>Sent:</B> Wednesday, January 22,
2003 11:27 AM<BR><B>To:</B> insight-users@public.kitware.com<BR><B>Subject:</B>
[Insight-users] Image Symilarity Metrics suggestion<BR><BR></DIV></FONT></FONT>
<BLOCKQUOTE dir=ltr
style="PADDING-LEFT: 5px; MARGIN-LEFT: 5px; BORDER-LEFT: #0000ff 2px solid; MARGIN-RIGHT: 0px">
<DIV><FONT face=Arial size=2><SPAN class=367230316-22012003>Hi
All,</SPAN></FONT></DIV>
<DIV><FONT face=Arial size=2><SPAN
class=367230316-22012003></SPAN></FONT> </DIV>
<DIV><FONT face=Arial size=2><SPAN class=367230316-22012003>I'm novice in
ITK programming and trying to understand the best way to do Image
comparison.</SPAN></FONT></DIV>
<DIV><FONT face=Arial size=2><SPAN class=367230316-22012003>The objective is
to build a keyframe grabbing for video contents and the problem to solve for
me is to compare two images and then get a measurement of the difference
between them.</SPAN></FONT></DIV>
<DIV><FONT face=Arial size=2><SPAN class=367230316-22012003>The analysis will
be done between two images in memory and not read from a file so in
which way can i convert a DIB image in to itk::Image?</SPAN></FONT></DIV>
<DIV><FONT face=Arial size=2><SPAN class=367230316-22012003>Can you help me
indicating a tutorial or an example or what ever you think could
help? </SPAN></FONT></DIV>
<DIV><FONT face=Arial size=2><SPAN class=367230316-22012003>Many thanks in
advance.</SPAN></FONT></DIV>
<DIV><FONT face=Arial size=2><SPAN
class=367230316-22012003>Regards.</SPAN></FONT></DIV>
<DIV><FONT face=Arial size=2><SPAN
class=367230316-22012003></SPAN></FONT> </DIV>
<DIV align=center>
<TABLE width="75%" border=0>
<TBODY>
<TR>
<TD height=14>
<DIV align=center><FONT face="Verdana, Arial, Helvetica, sans-serif"
size=2>Fabio Interlenghi </FONT></DIV></TD></TR>
<TR>
<TD height=14>
<DIV align=center><FONT face="Verdana, Arial, Helvetica, sans-serif"
size=1>Direzione Tecnica </FONT></DIV></TD></TR>
<TR>
<TD height=69>
<DIV align=center><FONT face="Verdana, Arial, Helvetica, sans-serif"
size=1><IMG height=54 src="cid:716021217@22012003-2c40"
width=266></FONT></DIV></TD></TR>
<TR>
<TD height=14>
<DIV align=center><FONT face="Verdana, Arial, Helvetica, sans-serif"
size=1>Media Businness Unit</FONT></DIV></TD></TR>
<TR>
<TD height=14>
<DIV align=center><FONT face="Verdana, Arial, Helvetica, sans-serif"
size=1><A
href="http://www.diapasonsrl.it/">http://www.diapasonsrl.it</A></FONT></DIV></TD></TR>
<TR>
<TD height=14>
<DIV align=center><FONT face="Verdana, Arial, Helvetica, sans-serif"
size=1>Via Torre Pellice, 17</FONT></DIV></TD></TR>
<TR>
<TD height=14>
<DIV align=center><FONT face="Verdana, Arial, Helvetica, sans-serif"
size=1>10156 Torino</FONT></DIV></TD></TR>
<TR>
<TD height=14>
<DIV align=center><FONT face="Verdana, Arial, Helvetica, sans-serif"
size=1>Tel.: 0112743095</FONT></DIV></TD></TR>
<TR>
<TD height=14>
<DIV align=center><FONT face="Verdana, Arial, Helvetica, sans-serif"
size=1>Fax : 0112735640</FONT></DIV></TD></TR>
<TR>
<TD height=14>
<DIV align=center><FONT face="Verdana, Arial, Helvetica, sans-serif"
size=1>Mob.: 3357887348</FONT></DIV></TD></TR></TBODY></TABLE><FONT
face="Verdana, Arial, Helvetica, sans-serif" size=1></FONT></DIV>
<DIV> </DIV></BLOCKQUOTE></BODY></HTML>
------_=_NextPart_001_01C2C239.6BED5ACA--
------_=_NextPart_000_01C2C239.6BED5ACA
Content-Type: image/jpeg;
name="DiaLogo_conNome_Beveled_Alabarde.jpg"
Content-Transfer-Encoding: base64
Content-Disposition: attachment;
filename="DiaLogo_conNome_Beveled_Alabarde.jpg"
Content-ID: <716021217@22012003-2c40>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------_=_NextPart_000_01C2C239.6BED5ACA--