Mercurial > hg > octave-image
annotate inst/regionprops.m @ 561:c45838839d86
maint: update license to GPLv3 and mention non GPL files
| author | carandraug |
|---|---|
| date | Mon, 16 Apr 2012 12:49:47 +0000 |
| parents | 39a521b5484e |
| children | 67d43bf75000 |
| rev | line source |
|---|---|
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1 ## Copyright (C) 2010 Soren Hauberg <soren@hauberg.org> |
| 393 | 2 ## |
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3 ## This program is free software; you can redistribute it and/or modify it under |
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4 ## the terms of the GNU General Public License as published by the Free Software |
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5 ## Foundation; either version 3 of the License, or (at your option) any later |
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6 ## version. |
| 393 | 7 ## |
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8 ## This program is distributed in the hope that it will be useful, but WITHOUT |
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9 ## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or |
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10 ## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more |
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11 ## details. |
| 393 | 12 ## |
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13 ## You should have received a copy of the GNU General Public License along with |
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14 ## this program; if not, see <http://www.gnu.org/licenses/>. |
| 393 | 15 |
| 16 ## -*- texinfo -*- | |
| 17 ## @deftypefn {Function File} {@var{props} = } regionprops (@var{BW}) | |
| 18 ## @deftypefnx {Function File} {@var{props} = } regionprops (@var{BW}, @var{properties}, @dots{}) | |
| 19 ## Compute object properties in a binary image. | |
| 20 ## | |
| 21 ## @code{regionprops} computes various properties of the individual objects (as | |
| 22 ## identified by @code{bwlabel}) in the binary image @var{BW}. The result is a | |
| 23 ## structure array containing an entry per property per object. | |
| 24 ## | |
| 25 ## The following properties can be computed. | |
| 26 ## | |
| 27 ## @table @t | |
| 28 ## @item "Area" | |
| 29 ## The number of pixels in the object. | |
| 30 ## @item "EulerNumber" | |
| 31 ## @itemx "euler_number" | |
| 32 ## The Euler number of the object (see @code{bweuler} for details). | |
| 33 ## @item "BoundingBox" | |
| 34 ## @itemx "bounding_box" | |
| 35 ## The bounding box of the object. This is represented as a 4-vector where the | |
| 36 ## first two entries are the @math{x} and @math{y} coordinates of the upper left | |
| 37 ## corner of the bounding box, and the two last entries are the width and the | |
| 38 ## height of the box. | |
| 39 ## @item "Extent" | |
| 40 ## The area of the object divided by the area of the bounding box. | |
| 41 ## @item "Perimeter" | |
| 42 ## The length of the boundary of the object. | |
| 43 ## @item "Centroid" | |
| 44 ## The center coordinate of the object. | |
| 45 ## @item "PixelIdxList" | |
| 46 ## @itemx "pixel_idx_list" | |
| 47 ## The indices of the pixels in the object. | |
| 48 ## @item "FilledArea" | |
| 49 ## @itemx "filled_area" | |
| 50 ## The area of the object including possible holes. | |
| 51 ## @item "PixelList" | |
| 52 ## @itemx "pixel_list" | |
| 53 ## The actual pixel values inside the object. This is only useful for grey scale | |
| 54 ## images. | |
| 55 ## @item "FilledImage" | |
| 56 ## @itemx "filled_image" | |
| 57 ## A binary image with the same size as the object's bounding box that contains | |
| 58 ## the object with all holes removed. | |
| 59 ## @item "Image" | |
| 60 ## An image with the same size as the bounding box that contains the original pixels. | |
| 61 ## @item "MaxIntensity" | |
| 62 ## @itemx "max_intensity" | |
| 63 ## The maximum intensity inside the object. | |
| 64 ## @item "MinIntensity" | |
| 65 ## @itemx "min_intensity" | |
| 66 ## The minimum intensity inside the object. | |
| 67 ## @item "WeightedCentroid" | |
| 68 ## @itemx "weighted_centroid" | |
| 69 ## The centroid of the object where pixel values are used as weights. | |
| 70 ## @item "MeanIntensity" | |
| 71 ## @itemx "mean_intensity" | |
| 72 ## The mean intensity inside the object. | |
| 73 ## @item "PixelValues" | |
| 74 ## @itemx "pixel_values" | |
| 75 ## The pixel values inside the object represented as a vector. | |
| 76 ## @end table | |
| 77 ## | |
| 78 ## The requested properties can either be specified as several input arguments | |
| 79 ## or as a cell array of strings. As a short-hand it is also possible to give | |
| 80 ## the following strings as arguments. | |
| 81 ## | |
| 82 ## @table @t | |
| 83 ## @item "basic" | |
| 84 ## The following properties are computed: @t{"Area"}, @t{"Centroid"} and @t{"BoundingBox"}. | |
| 85 ## @item "all" | |
| 86 ## All properties are computed. | |
| 87 ## @end table | |
| 88 ## | |
| 89 ## If no properties are given, @t{basic} is assumed. | |
| 90 ## @seealso{bwlabel, bwperim, bweuler} | |
| 91 ## @end deftypefn | |
| 92 | |
| 93 function retval = regionprops (bw, varargin) | |
| 94 ## Check input | |
| 95 if (nargin < 1) | |
| 96 error ("regionprops: not enough input arguments"); | |
| 97 endif | |
| 98 | |
| 99 if (!ismatrix (bw) || ndims (bw) != 2) | |
| 100 error ("regionprops: first input argument must be a NxM matrix"); | |
| 101 endif | |
| 102 | |
| 103 if (numel (varargin) == 0) | |
| 104 properties = "basic"; | |
| 105 elseif (numel (varargin) == 1 && iscellstr (varargin {1})) | |
| 106 properties = varargin {1}; | |
| 107 elseif (iscellstr (varargin)) | |
| 108 properties = varargin; | |
| 109 else | |
| 110 error ("regionprops: properties must be a cell array of strings"); | |
| 111 endif | |
| 112 | |
| 113 if (ischar (properties) && strcmpi (properties, "basic")) | |
| 114 properties = {"Area", "Centroid", "BoundingBox"}; | |
| 115 elseif (ischar (properties) && strcmpi (properties, "all")) | |
| 116 properties = {"area", "eulernumber", "boundingbox", "extent", "perimeter", ... | |
| 117 "centroid", "pixelidxlist", "filledarea", "pixellist", ... | |
| 118 "filledimage", "image", "maxintensity", "minintensity", ... | |
| 119 "weightedcentroid", "meanintensity", "pixelvalues"}; | |
| 120 elseif (!iscellstr (properties)) | |
| 121 error ("%s %s", "regionprops: properties must be specified as a list of", | |
| 122 "strings or a cell array of strings"); | |
| 123 endif | |
| 124 | |
| 125 ## Get a labelled image | |
| 126 if (!islogical (bw) && all (bw >= 0) && all (bw == round (bw))) | |
| 127 L = bw; # the image was already labelled | |
| 128 num_labels = max (L (:)); | |
| 129 else | |
| 396 | 130 [L, num_labels] = bwlabel (bw); |
| 393 | 131 endif |
| 132 | |
| 133 ## Compute the properties | |
| 134 retval = struct (); | |
| 135 for k = 1:numel (properties) | |
| 136 switch (lower (properties {k})) | |
| 137 case "area" | |
| 138 for k = 1:num_labels | |
| 139 retval (k).Area = local_area (L == k); | |
| 140 endfor | |
| 141 | |
| 142 case {"eulernumber", "euler_number"} | |
| 143 for k = 1:num_labels | |
| 144 retval (k).EulerNumber = bweuler (L == k); | |
| 145 endfor | |
| 146 | |
| 147 case {"boundingbox", "bounding_box"} | |
| 148 for k = 1:num_labels | |
| 149 retval (k).BoundingBox = local_boundingbox (L == k); | |
| 150 endfor | |
| 151 | |
| 152 case "extent" | |
| 153 for k = 1:num_labels | |
| 154 bb = local_boundingbox (L == k); | |
| 155 area = local_area (L == k); | |
| 156 retval (k).Extent = area / (bb (3) * bb (4)); | |
| 157 endfor | |
| 158 | |
| 159 case "perimeter" | |
| 160 for k = 1:num_labels | |
| 161 retval (k).Perimeter = sum (bwperim (L == k) (:)); | |
| 162 endfor | |
| 163 | |
| 164 case "centroid" | |
| 165 for k = 1:num_labels | |
| 166 [Y, X] = find (L == k); | |
| 167 retval (k).Centroid = [mean(X), mean(Y)]; | |
| 168 endfor | |
| 169 | |
| 170 case {"pixelidxlist", "pixel_idx_list"} | |
| 171 for k = 1:num_labels | |
| 172 retval (k).PixelIdxList = find (L == k); | |
| 173 endfor | |
| 174 | |
| 175 case {"filledarea", "filled_area"} | |
| 176 for k = 1:num_labels | |
| 177 retval (k).FilledArea = sum (bwfill (L == k, "holes") (:)); | |
| 178 endfor | |
| 179 | |
| 180 case {"pixellist", "pixel_list"} | |
| 181 for k = 1:num_labels | |
| 182 [Y, X] = find (L == k); | |
| 183 retval (k).PixelList = [X, Y]; | |
| 184 endfor | |
| 185 | |
| 186 case {"filledimage", "filled_image"} | |
| 187 for k = 1:num_labels | |
| 188 retval (k).FilledImage = bwfill (L == k, "holes"); | |
| 189 endfor | |
| 190 | |
| 191 case "image" | |
| 192 for k = 1:num_labels | |
| 193 tmp = (L == k); | |
| 194 [R, C] = find (tmp); | |
| 195 retval (k).Image = tmp (min (R):max (R), min (C):max (C)); | |
| 196 endfor | |
| 197 | |
| 198 case {"maxintensity", "max_intensity"} | |
| 199 for k = 1:num_labels | |
| 200 retval (k).MaxIntensity = max (bw (L == k) (:)); | |
| 201 endfor | |
| 202 | |
| 203 case {"minintensity", "min_intensity"} | |
| 204 for k = 1:num_labels | |
| 205 retval (k).MaxIntensity = min (bw (L == k) (:)); | |
| 206 endfor | |
| 207 | |
| 208 case {"weightedcentroid", "weighted_centroid"} | |
| 209 for k = 1:num_labels | |
| 210 [Y, X] = find (L == k); | |
| 211 vals = bw (L == k) (:); | |
| 212 vals /= sum (vals); | |
| 213 retval (k).WeightedCentroid = [dot(X, vals), dot(Y, vals)]; | |
| 214 endfor | |
| 215 | |
| 216 case {"meanintensity", "mean_intensity"} | |
| 217 for k = 1:num_labels | |
| 218 retval (k).MaxIntensity = mean (bw (L == k) (:)); | |
| 219 endfor | |
| 220 | |
| 221 case {"pixelvalues", "pixel_values"} | |
| 222 for k = 1:num_labels | |
| 223 retval (k).PixelValues = bw (L == k)(:); | |
| 224 endfor | |
| 225 | |
| 396 | 226 case "orientation" |
| 227 for k = 1:num_labels | |
| 228 [Y, X] = find (L == k); | |
| 229 if (numel (Y) > 1) | |
| 230 C = cov ([X(:), Y(:)]); | |
| 231 [V, lambda] = eig (C); | |
| 232 [max_val, max_idx] = max (diag (lambda)); | |
| 233 v = V (:, max_idx); | |
| 234 retval (k).Orientation = 180 - 180 * atan2 (v (2), v (1)) / pi; | |
| 235 else | |
| 236 retval (k).Orientation = 0; # XXX: What does the other brand do? | |
| 237 endif | |
| 238 endfor | |
| 239 | |
| 240 %{ | |
| 241 case "majoraxislength" | |
| 242 for k = 1:num_labels | |
| 243 [Y, X] = find (L == k); | |
| 244 if (numel (Y) > 1) | |
| 245 C = cov ([X(:), Y(:)]); | |
| 246 lambda = eig (C); | |
| 247 retval (k).MajorAxisLength = (max (lambda)); | |
| 248 else | |
| 249 retval (k).MajorAxisLength = 1; | |
| 250 endif | |
| 251 endfor | |
| 252 | |
| 253 case "minoraxislength" | |
| 254 for k = 1:num_labels | |
| 255 [Y, X] = find (L == k); | |
| 256 if (numel (Y) > 1) | |
| 257 C = cov ([X(:), Y(:)]); | |
| 258 lambda = eig (C); | |
| 259 retval (k).MinorAxisLength = (min (lambda)); | |
| 260 else | |
| 261 retval (k).MinorAxisLength = 1; | |
| 262 endif | |
| 263 endfor | |
| 264 %} | |
| 265 | |
| 393 | 266 #case "extrema" |
| 267 #case "convexarea" | |
| 268 #case "convexhull" | |
| 269 #case "solidity" | |
| 270 #case "conveximage" | |
| 271 #case "subarrayidx" | |
| 272 #case "eccentricity" | |
| 273 #case "equivdiameter" | |
| 274 | |
| 275 otherwise | |
| 276 error ("regionprops: unsupported property '%s'", properties {k}); | |
| 277 endswitch | |
| 278 endfor | |
| 279 endfunction | |
| 280 | |
| 281 function retval = local_area (bw) | |
| 282 retval = sum (bw (:)); | |
| 283 endfunction | |
| 284 | |
| 285 function retval = local_boundingbox (bw) | |
| 286 [Y, X] = find (bw); | |
| 287 retval = [min(X)-0.5, min(Y)-0.5, max(X)-min(X)+1, max(Y)-min(Y)+1]; | |
| 288 endfunction |