BNW using Octave instead of Matlab.

This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning.

I am calling this BNW_1.02. It can be accessed at:
compbio.uthsc.edu/BNW_1.02

1 files changed, 42 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/KPMtools/nonmaxsup.m b/sourcecodes/bnt-master/KPMtools/nonmaxsup.m
new file mode 100644
index 00000000..f94d4560
--- /dev/null
+++ b/sourcecodes/bnt-master/KPMtools/nonmaxsup.m
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+% NONMAXSUP - Non-maximal Suppression
+%
+% Usage:  cim = nonmaxsup(im, radius)
+%
+% Arguments:   
+%            im     - image to be processed.
+%            radius - radius of region considered in non-maximal
+%                     suppression (optional). Typical values to use might
+%                     be 1-3.  Default is 1.
+%
+% Returns:
+%            cim    - image with pixels that are not maximal within a 
+%                     square neighborhood zeroed out.
+
+% Copyright (C) 2002 Mark A. Paskin
+%
+% This program is free software; you can redistribute it and/or modify
+% it under the terms of the GNU General Public License as published by
+% the Free Software Foundation; either version 2 of the License, or
+% (at your option) any later version.
+%
+% This program is distributed in the hope that it will be useful, but
+% WITHOUT ANY WARRANTY; without even the implied warranty of
+% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+% General Public License for more details.
+%
+% You should have received a copy of the GNU General Public License
+% along with this program; if not, write to the Free Software
+% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307
+% USA.
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+function cim = nonmaxsup(m, radius)
+  if (nargin == 1) radius = 1; end
+  % Extract local maxima by performing a grey scale morphological
+  % dilation and then finding points in the corner strength image that
+  % match the dilated image and are also greater than the threshold.
+  sze = 2 * radius + 1;                   % Size of mask.
+  mx = ordfilt2(m, sze^2, ones(sze));   % Grey-scale dilate.
+  cim = sparse(m .* (m == mx));
+
+