regionprops does a bunch of things, most of which make sense for
N-dimensional images. I attach a proposed diff to address this. Can
anyone give me some review before I commit it?
TIA,
- Jordi G. H.
Index: regionprops.m
===================================================================
--- regionprops.m (revision 10831)
+++ regionprops.m (working copy)
@@ -96,10 +96,6 @@
error ("regionprops: not enough input arguments");
endif
- if (!ismatrix (bw) || ndims (bw) != 2)
- error ("regionprops: first input argument must be a NxM matrix");
- endif
-
if (numel (varargin) == 0)
properties = "basic";
elseif (numel (varargin) == 1 && iscellstr (varargin {1}))
@@ -113,12 +109,13 @@
if (ischar (properties) && strcmpi (properties, "basic"))
properties = {"Area", "Centroid", "BoundingBox"};
elseif (ischar (properties) && strcmpi (properties, "all"))
- properties = {"area", "eulernumber", "boundingbox", "extent", "perimeter", ...
- "centroid", "pixelidxlist", "filledarea", "pixellist", ...
- "filledimage", "image", "maxintensity", "minintensity", ...
+ properties = {"area", "eulernumber", "boundingbox", "extent", "perimeter",
+ "centroid", "pixelidxlist", "filledarea", "pixellist",
+ "filledimage", "image", "maxintensity", "minintensity",
"weightedcentroid", "meanintensity", "pixelvalues"};
elseif (!iscellstr (properties))
- error ("%s %s", "regionprops: properties must be specified as a list of",
+ error ("%s %s", "regionprops: properties must be specified as a \
+ %list of",
"strings or a cell array of strings");
endif
@@ -127,7 +124,10 @@
L = bw; # the image was already labelled
num_labels = max (L (:));
else
- [L, num_labels] = bwlabel (bw);
+ if (ndims (bw) == 2)
+ [L, num_labels] = bwlabel (bw);
+ else
+ [L, num_labels] = bwlabeln (bw);
endif
## Compute the properties
@@ -138,6 +138,9 @@
for k = 1:num_labels
retval (k).Area = local_area (L == k);
endfor
+ if num_labels == 0
+ retval = struct("Area", {});
+ endif
case {"eulernumber", "euler_number"}
for k = 1:num_labels
@@ -163,8 +166,8 @@
case "centroid"
for k = 1:num_labels
- [Y, X] = find (L == k);
- retval (k).Centroid = [mean(X), mean(Y)];
+ C = cell2mat (nthargout (1:ndims(L), @find, L == k));
+ retval (k).Centroid = [mean(C)];
endfor
case {"pixelidxlist", "pixel_idx_list"}
@@ -179,8 +182,8 @@
case {"pixellist", "pixel_list"}
for k = 1:num_labels
- [Y, X] = find (L == k);
- retval (k).PixelList = [X, Y];
+ X = cell2mat (nthargout (1:ndims(bw), @find, L == k));
+ retval (k).PixelList = [X(2), X(1), X(3:)];
endfor
case {"filledimage", "filled_image"}
@@ -202,20 +205,21 @@
case {"minintensity", "min_intensity"}
for k = 1:num_labels
- retval (k).MaxIntensity = min (bw (L == k) (:));
+ retval (k).MinIntensity = min (bw (L == k) (:));
endfor
case {"weightedcentroid", "weighted_centroid"}
for k = 1:num_labels
- [Y, X] = find (L == k);
+ C = cell2mat (nthargout(1:ndims(bw), @find, L == k));
vals = bw (L == k) (:);
vals /= sum (vals);
- retval (k).WeightedCentroid = [dot(X, vals), dot(Y, vals)];
+ retval (k).WeightedCentroid = [dot(C(2), vals), dot(C(1)), vals),\
+ dot(C(3:end), repmat(vals, 1, length(C)-2)];
endfor
case {"meanintensity", "mean_intensity"}
for k = 1:num_labels
- retval (k).MaxIntensity = mean (bw (L == k) (:));
+ retval (k).MeanIntensity = mean (bw (L == k) (:));
endfor
case {"pixelvalues", "pixel_values"}
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