Fwd: Phansalkar local thresholding

[Kenneth Sloan]

Can someone please point me at any published descriptions of the method, testing, or use of the “Phansalkar” method of local thresholding?  I see one reference in the ImageJ docs; I’m looking for more.

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Kenneth Sloan
[hidden email]

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[Gabriel Landini]

On Wednesday 23 Apr 2014 08:33:53 you wrote:
> Can someone please point me at any published descriptions of the method,
> testing, or use of the “Phansalkar” method of local thresholding?  I see
> one reference in the ImageJ docs; I’m looking for more.

From the Auto Local Threshold info:
http://www.mecourse.com/landinig/software/autothreshold/autothreshold.html

Phansalkar
This is a modification of Sauvola's thresholding method to deal with low
contrast images.

1. Phansalskar N. et al. Adaptive local thresholding for detection of nuclei
in diversity stained cytology images. International Conference on
Communications and Signal Processing (ICCSP), 2011, 218-220.

In this method, the threshold t is computed as:

t = mean * (1 + p * exp(-q * mean) + k * ((stdev / r) - 1))

where mean and stdev are the local mean and standard deviation respectively.
Phansalkar recommends k = 0.25, r = 0.5, p = 2 and q = 10. In this plugin, k
and r are the parameters 1 and 2 respectively, but the values of p and q are
fixed.
Parameter 1: is the k value. The default value is 0.25. Any other number than
0 will change its value.
Parameter 2: is the r value. The default value is 0.5. This value is different
from Sauvola's because it uses the normalised intensity of the image. Any
other number than 0 will change its value
Implemented from Phansalkar's paper description, although this version uses a
circular rather than rectangular local window.

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[Kenneth Sloan]

Yes -as stated, I already have that info.  The question was:  is there more?

-Kenneth Sloan
(von meinem iPhone4S gesendet)

> On Apr 23, 2014, at 9:30, Gabriel Landini <[hidden email]> wrote:
>
>> On Wednesday 23 Apr 2014 08:33:53 you wrote:
>> Can someone please point me at any published descriptions of the method,
>> testing, or use of the “Phansalkar” method of local thresholding?  I see
>> one reference in the ImageJ docs; I’m looking for more.
>
> From the Auto Local Threshold info:
> http://www.mecourse.com/landinig/software/autothreshold/autothreshold.html
>
> Phansalkar
> This is a modification of Sauvola's thresholding method to deal with low
> contrast images.
>
> 1. Phansalskar N. et al. Adaptive local thresholding for detection of nuclei
> in diversity stained cytology images. International Conference on
> Communications and Signal Processing (ICCSP), 2011, 218-220.
>
> In this method, the threshold t is computed as:
>
> t = mean * (1 + p * exp(-q * mean) + k * ((stdev / r) - 1))
>
> where mean and stdev are the local mean and standard deviation respectively.
> Phansalkar recommends k = 0.25, r = 0.5, p = 2 and q = 10. In this plugin, k
> and r are the parameters 1 and 2 respectively, but the values of p and q are
> fixed.
> Parameter 1: is the k value. The default value is 0.25. Any other number than
> 0 will change its value.
> Parameter 2: is the r value. The default value is 0.5. This value is different
> from Sauvola's because it uses the normalised intensity of the image. Any
> other number than 0 will change its value
> Implemented from Phansalkar's paper description, although this version uses a
> circular rather than rectangular local window.
>
> --
> ImageJ mailing list: http://imagej.nih.gov/ij/list.html

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[ctrueden]

Hi Ken,

> Yes -as stated, I already have that info.  The question was:  is there
more?

The paper is cached online in PDF and HTML at:
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5739305

But whether you can access the full text hinges on whether your university
provides such access. I was able to download it here at UW-Madison.

Regards,
Curtis


On Wed, Apr 23, 2014 at 1:04 PM, Kenneth Sloan <[hidden email]> wrote:

> Yes -as stated, I already have that info.  The question was:  is there
> more?
>
> -Kenneth Sloan
> (von meinem iPhone4S gesendet)
>
> > On Apr 23, 2014, at 9:30, Gabriel Landini <[hidden email]> wrote:
> >
> >> On Wednesday 23 Apr 2014 08:33:53 you wrote:
> >> Can someone please point me at any published descriptions of the method,
> >> testing, or use of the “Phansalkar” method of local thresholding?  I see
> >> one reference in the ImageJ docs; I’m looking for more.
> >
> > From the Auto Local Threshold info:
> >
> http://www.mecourse.com/landinig/software/autothreshold/autothreshold.html
> >
> > Phansalkar
> > This is a modification of Sauvola's thresholding method to deal with low
> > contrast images.
> >
> > 1. Phansalskar N. et al. Adaptive local thresholding for detection of
> nuclei
> > in diversity stained cytology images. International Conference on
> > Communications and Signal Processing (ICCSP), 2011, 218-220.
> >
> > In this method, the threshold t is computed as:
> >
> > t = mean * (1 + p * exp(-q * mean) + k * ((stdev / r) - 1))
> >
> > where mean and stdev are the local mean and standard deviation
> respectively.
> > Phansalkar recommends k = 0.25, r = 0.5, p = 2 and q = 10. In this
> plugin, k
> > and r are the parameters 1 and 2 respectively, but the values of p and q
> are
> > fixed.
> > Parameter 1: is the k value. The default value is 0.25. Any other number
> than
> > 0 will change its value.
> > Parameter 2: is the r value. The default value is 0.5. This value is
> different
> > from Sauvola's because it uses the normalised intensity of the image. Any
> > other number than 0 will change its value
> > Implemented from Phansalkar's paper description, although this version
> uses a
> > circular rather than rectangular local window.
> >
> > --
> > ImageJ mailing list: http://imagej.nih.gov/ij/list.html
>
> --
> ImageJ mailing list: http://imagej.nih.gov/ij/list.html
>

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