[Insight-users] Clear image borders
David Llanos
gva02 at elai.upm.es
Mon, 29 Mar 2004 17:57:45 +0200
This is a multi-part message in MIME format.
------=_NextPart_000_0008_01C415B7.572E3120
Content-Type: multipart/alternative;
boundary="----=_NextPart_001_0009_01C415B7.572E3120"
------=_NextPart_001_0009_01C415B7.572E3120
Content-Type: text/plain;
charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
Hi all,
I am working in a project where I carry out processing of sperm. For =
they give me to it pictures and I have to return characteristic as =
density, radio of the halo, radio of the core, etc.. The problem this in =
that in the pictures some sperms come cut, and these they should be =
eliminated. =20
=20
I wonder if in ITK some class exists with the one that can eliminate =
parts of an image, in short those that are cut by the border of the =
image. =20
=20
To clarify my problem I attach you three images:
1. - original.jpg The original image =20
2. - process.jpg The processing image =20
3. - clearborder.jpg The image without cut sperms =20
Thanks in advange and regards.
David.
-------------------------------------------------------------------------=
-------------------------------------------------------------------------=
----
NOTA: in MATLAB the procedure that makes this function is =
"imgclearborder", I attach you the example:
imgEspermasRGB =3D imread ( NomFichImg );
hist =3D imhist(imgEspermasRGB(:,:,2)); %Componente del verde
umbralEspermas =3D =
BIN_EntropiaKSW(hist,size(imgEspermasRGB,1)*size(imgEspermasRGB,2));=20
seEspermas =3D strel('disk',20);
imgEsperBW =3D imclearborder(...
=
imopen((imgEspermasRGB(:,:,2)<umbralEspermas),seEspermas));
-------------------------------------------------------------------------=
-------------------------------------------------------------------------=
----
PD: if it interests you to some I send you the function BIN_EntropiaKSW, =
necessary to run the application, in MATLAB or in C
------=_NextPart_001_0009_01C415B7.572E3120
Content-Type: text/html;
charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN">
<HTML><HEAD>
<META http-equiv=3DContent-Type content=3D"text/html; =
charset=3Diso-8859-1">
<META content=3D"MSHTML 6.00.2800.1400" name=3DGENERATOR>
<STYLE></STYLE>
</HEAD>
<BODY bgColor=3D#ffffff>
<DIV><BR> </DIV>
<DIV><FONT face=3DArial size=3D2>Hi all,</FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2>I am working in a project where I carry =
out=20
processing of sperm. For they give me to it pictures and I have to =
return=20
characteristic as density, radio of the halo, radio of the core, etc.. =
The=20
problem this in that in the pictures some sperms come cut, and these =
they should=20
be eliminated. <BR> <BR>I wonder if in ITK some class exists =
with=20
the one that can eliminate parts of an image, in short those that are =
cut by the=20
border of the image. <BR> <BR>To clarify my problem I attach =
you=20
three images:</FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2>1. - original.jpg =
=20
The original image <BR>2. -=20
process.jpg The =
processing=20
image <BR>3. -=20
clearborder.jpg The image without cut =
sperms =20
</FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2>Thanks in advange and =
regards.</FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2>David.</FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial=20
size=3D2>----------------------------------------------------------------=
-------------------------------------------------------------------------=
-------------</FONT></DIV>
<DIV><FONT face=3DArial size=3D2>NOTA: in MATLAB the procedure that =
makes this=20
function is "imgclearborder", I attach you the example:</FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2>imgEspermasRGB =3D imread ( NomFichImg =
);</FONT><FONT=20
face=3DArial size=3D2><BR>hist =3D imhist(imgEspermasRGB(:,:,2)); =
%Componente del=20
verde<BR>umbralEspermas =3D=20
BIN_EntropiaKSW(hist,size(imgEspermasRGB,1)*size(imgEspermasRGB,2));=20
</FONT></DIV>
<DIV><FONT face=3DArial size=3D2>seEspermas =3D strel('disk',20);</DIV>
<DIV>imgEsperBW =3D=20
imclearborder(...<BR> &nbs=
p; =20
imopen((imgEspermasRGB(:,:,2)<umbralEspermas),seEspermas));</DIV>
<DIV>--------------------------------------------------------------------=
-------------------------------------------------------------------------=
---------</DIV>
<DIV> </DIV>
<DIV>PD: if it interests you to some I send you the function =
BIN_EntropiaKSW,=20
necessary to run the application, in MATLAB or in =
C</FONT></DIV></BODY></HTML>
------=_NextPart_001_0009_01C415B7.572E3120--
------=_NextPart_000_0008_01C415B7.572E3120
Content-Type: image/jpeg;
name="original.jpg"
Content-Transfer-Encoding: base64
Content-Disposition: attachment;
filename="original.jpg"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------=_NextPart_000_0008_01C415B7.572E3120
Content-Type: image/jpeg;
name="process.jpg"
Content-Transfer-Encoding: base64
Content-Disposition: attachment;
filename="process.jpg"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------=_NextPart_000_0008_01C415B7.572E3120
Content-Type: image/jpeg;
name="clearborder.jpg"
Content-Transfer-Encoding: base64
Content-Disposition: attachment;
filename="clearborder.jpg"
/9j/4AAQSkZJRgABAQEBLAEsAAD/2wBDAAMCAgMCAgMDAwMEAwMEBQgFBQQEBQoHBwYIDAoMDAsK
CwsNDhIQDQ4RDgsLEBYQERMUFRUVDA8XGBYUGBIUFRT/2wBDAQMEBAUEBQkFBQkUDQsNFBQUFBQU
FBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBT/wAARCACHALQDASIA
AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA
AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3
ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm
p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA
AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx
BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK
U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3
uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD9U6KK
KACikJA6nFG4eooAWik3D1FG4eooAWik3D1FG4eooAWik3D1FG4eooAWik3D1FG4eooAWik3D1FG
4eooAWik3D1FG4eooAWik3D1FG4eooAWik3D1FG4eooAWiiigAooooAKKKKAPgD/AILV/wDJrHhb
/sc7X/0hvq/Fav2p/wCC1f8Ayax4W/7HO1/9Ib6vxWoAKKKKACiiigAooooAKKKKACiiigAooooA
KKKKACiiigD+qiiiigAooooAKKKKAPgD/gtX/wAmseFv+xztf/SG+r8Vq/an/gtX/wAmseFv+xzt
f/SG+r8VqADrX61fso/8EhPC998N4/EHxhu9Qvda8Q6Mj22h2iy2Enh+SUFg7s3zSXKKYxskjEaO
JVZJhtYfmp+z34Y0vxt8fPhr4d1y2+26Jq/ibTNPvrYyNH5tvLdRxyJuQhlyrMMqQRngg1/TTQB8
v/Hj/gnN8EvjV4NuNMsvBmj+A9cjhkGna54Z0+Oze2lYod0kMWxLhfkAKyAkKz7GjZtw/EL9pP4H
X37N/wAbfFHw71DUoNXm0aaMR39spRZ4ZYkmicoclGMciblyQrZAZgAx/pdr8lP+C4v9h/8ACV/C
X7P/AGf/AMJJ9i1L7d5Xl/bPsu+3+zebj5/L3/atm75d3nbed1AH5hUUUUAFFFFABRRRQAUUUUAF
FFFABRRRQB/VRRRRQAUUUUAFFFFAHwB/wWr/AOTWPC3/AGOdr/6Q31fitX7U/wDBav8A5NY8Lf8A
Y52v/pDfV+K1AADg1+uX7LH/AAWI0fWraz0H42WsHh6ey0xmm8YWommXUrlZEVFNlBbt5TPGzMzB
tm6NsKgdVX8jaKAP3S+IX/BXL4BeEbXSrjQdX1DxwJrzyb610vTrm2uLWDyZGE6C6jijk/eLEhTz
FIEhYZ2bT+O/7SPxvvf2j/jb4p+I2oaZBo0+tzRsthbSNIsEUUKQxKXOC7COJNzYUM24hVBCj0r/
AIdvftJf8It/wkH/AAq3UPsH2L7f5P220+2eXs37fsvnef5uOPK2eZu+Xbu4r511bSb7QNVvdM1O
yuNO1Kyme2urO7iaKaCVGKvG6MAVZWBBUgEEEGgCrRRRQAUVa0nSb7XtVs9M0yzuNR1K9mS2tbO0
iaWaeV2CpGiKCWZmIAUAkkgCv0V+EH/BFjxp4v8ABcep+PfGsHw916Wd1XQ4dOTVWihHCtJNHcog
Zjk7ULgLtJbcSqAH5wUV+i3x0/4I1eLfhv8ADjUPEfgrxkfiLqthiabQYtFNncTW4VjI0GJ5fNlH
ykRYBYbgpLbUb89NY0e/8PateaXqtlc6ZqdlM9vdWV5E0U0EqEq6OjAFWBBBBAIIoAqUUUUAFFFF
ABRRRQB/VRRRRQAUUUUAFFFFAHwB/wAFq/8Ak1jwt/2Odr/6Q31fitX7U/8ABav/AJNY8Lf9jna/
+kN9X4rUAFfb3/BIDwF4d8cftYXE3iDSrfVZNB8Pz6xpgugWW3vUubWOOYLnDMiyyFdwO1sOMMqs
PiGu0+DHxd8Q/Ab4n+H/AB74Wktk1zRZzLAt5CJoZFZGjkjdTg7Xjd0JUqwDEqysAwAP6dK/GH/g
sj8B/Dnw1+LXhTxx4ftYNMl8bQ3janZW0RRJLy3eIvdH5sb5RcoGCquWiLnc0jGvftM/4LcfDqXw
a9zqHw88UWvisQzMul201tNYmUFvKU3bOjhWATc3kErubCvtG781/wBqr9pnxF+1f8W7vxt4gtrf
To1hWx0zS7bDJY2aO7RxF8AytmR2aRgNzO2Ai7UUA8fooooA+9P+CP8A8DvD3xN+PWp+Ldce4nuP
BEMN9p2nnTjNaTXEvmIss0zIyRtFjfGmVkZ8SIcQOK/bSvwt/wCCXP7Wuh/s1/FPWdC8VJ5Ph3xq
bGzbUlCL9huo5ikUs0kkqJHbhLicyNhiNqEcBs/uRpWq2Wu6XZ6lpt5b6hp15ClxbXlpKssM8TqG
SRHUkMrKQQQcEEEUAWq/Bb/gqp8HtL+En7XOsTaRJi18W2Ufid7ba3+jzzyzRzjczsX3ywyTZ+UD
ztgUBAT+5Pj/AMfeHvhb4M1fxZ4r1WDRPD2lQG4vL65J2xrkAAAZLMxIVUUFmZlVQSQD+AH7ff7Q
1j+0v+0vr/ijQ72e+8KWkMGlaJJc2q27/ZolyzBcBirzvcSKZPn2yKGC42KAfO1FFFAH65/8EuP2
EPDr/C+b4nfE7wto/iafxTCo0TSdd0wzixs1dsztHMNhachGRghxEqFXxM6j9KdX0ew8QaTe6Xql
lb6jpt9A9tdWd1EskM8TqVeN0YEMrKSCDwQSK8V/YV8a2Pj79j74Sanp0VxDbweH7fSmW5VVYy2Y
+ySsArEbTJbuVOclSpIByB7tQB+IP/BUH9inwx+zHrvhXxN8PrHULHwh4g820uNPkEtxb6bdRLGV
C3Lszfv1MjCNyWzDKVJX5Y/hWv2S/wCC2ninTLT4CeBPDctwV1nUPEw1C2t9jEPBb2s0czbsbRta
6gGCcnfxnBx+NtAH9VFFFFABRRRQAUUUUAfAH/Bav/k1jwt/2Odr/wCkN9X4rV+1P/Bav/k1jwt/
2Odr/wCkN9X4rUAFFFFABRRRQAUUUUAFeheFf2ifir4F0G00Pw38S/F3h/RbQsbfTtL1y6treHcx
dtsaOFGWZmOByWJ6mvPaKAPVfjV+1P8AFf8AaHFqnxB8baj4gtLbYYrDEdtZq679sn2eFUiMgErj
zCu/adu7AAHlVFFABRRRQB+hf/BNH/goTo/wB0y4+GnxLuprXwVLPLe6ZrmJ7k6ZKy5e3aJdxEDs
pYGNflkdywYSs8f274q/4Kwfs3eHtCub/T/F2oeJ7qLbs0vS9Eu47ibLBTsNxHFF8oJY7pF4U4yc
A/gvRQB7r+2T+1Vf/tffFqDxleeH7fwzb2emw6VZ6dBctcskSPJIWklKqHYyTSHKogC7BglSzeFU
UUAf1UUUUUAFFFFABRRRQB8Af8Fq/wDk1jwt/wBjna/+kN9X4rV+1P8AwWr/AOTWPC3/AGOdr/6Q
31fitQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAH9VFFFFABRRRQAUUUUAfAH/AAWr
/wCTWPC3/Y52v/pDfV+K1f1UUUAfyr0V/VRRQB/KvRX9VFFAH8q9Ff1UUUAfyr0V/VRRQB/KvRX9
VFFAH8q9Ff1UUUAfyr0V/VRRQB/KvRX9VFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUU
UUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAf/9k=
------=_NextPart_000_0008_01C415B7.572E3120--