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77 </script> 78 79 </div> 80 </header> 81 <main class="container"> 82 <div class="magick-template"> 83<div class="magick-header"> 84<p class="text-center"><a href="feature.html#CannyEdgeImage">CannyEdgeImage</a> • <a href="feature.html#GetImageFeatures">GetImageFeatures</a> • <a href="feature.html#Use HoughLineImage">Use HoughLineImage</a> • <a href="feature.html#MeanShiftImage">MeanShiftImage</a></p> 85 86<h2><a href="../../api/MagickCore/feature_8c.html" id="CannyEdgeImage">CannyEdgeImage</a></h2> 87 88<p>CannyEdgeImage() uses a multi-stage algorithm to detect a wide range of edges in images.</p> 89 90<p>The format of the CannyEdgeImage method is:</p> 91 92<pre class="text"> 93Image *CannyEdgeImage(const Image *image,const double radius, 94 const double sigma,const double lower_percent, 95 const double upper_percent,ExceptionInfo *exception) 96</pre> 97 98<p>A description of each parameter follows:</p> 99 100<dd> 101</dd> 102 103<dd> </dd> 104<dl class="dl-horizontal"> 105<dt>image</dt> 106<dd>the image. </dd> 107 108<dd> </dd> 109<dt>radius</dt> 110<dd>the radius of the gaussian smoothing filter. </dd> 111 112<dd> </dd> 113<dt>sigma</dt> 114<dd>the sigma of the gaussian smoothing filter. </dd> 115 116<dd> </dd> 117<dt>lower_percent</dt> 118<dd>percentage of edge pixels in the lower threshold. </dd> 119 120<dd> </dd> 121<dt>upper_percent</dt> 122<dd>percentage of edge pixels in the upper threshold. </dd> 123 124<dd> </dd> 125<dt>exception</dt> 126<dd>return any errors or warnings in this structure. </dd> 127 128<dd> </dd> 129</dl> 130<h2><a href="../../api/MagickCore/feature_8c.html" id="GetImageFeatures">GetImageFeatures</a></h2> 131 132<p>GetImageFeatures() returns features for each channel in the image in each of four directions (horizontal, vertical, left and right diagonals) for the specified distance. The features include the angular second moment, contrast, correlation, sum of squares: variance, inverse difference moment, sum average, sum varience, sum entropy, entropy, difference variance, difference entropy, information measures of correlation 1, information measures of correlation 2, and maximum correlation coefficient. You can access the red channel contrast, for example, like this:</p> 133 134<pre class="text"> 135channel_features=GetImageFeatures(image,1,exception); 136contrast=channel_features[RedPixelChannel].contrast[0]; 137</pre> 138 139<p>Use MagickRelinquishMemory() to free the features buffer.</p> 140 141<p>The format of the GetImageFeatures method is:</p> 142 143<pre class="text"> 144ChannelFeatures *GetImageFeatures(const Image *image, 145 const size_t distance,ExceptionInfo *exception) 146</pre> 147 148<p>A description of each parameter follows:</p> 149 150<dd> 151</dd> 152 153<dd> </dd> 154<dl class="dl-horizontal"> 155<dt>image</dt> 156<dd>the image. </dd> 157 158<dd> </dd> 159<dt>distance</dt> 160<dd>the distance. </dd> 161 162<dd> </dd> 163<dt>exception</dt> 164<dd>return any errors or warnings in this structure. </dd> 165 166<dd> </dd> 167</dl> 168<h2><a href="../../api/MagickCore/feature_8c.html" id="Use_HoughLineImage">Use HoughLineImage</a></h2> 169 170<p>Use HoughLineImage() in conjunction with any binary edge extracted image (we recommand Canny) to identify lines in the image. The algorithm accumulates counts for every white pixel for every possible orientation (for angles from 0 to 179 in 1 degree increments) and distance from the center of the image to the corner (in 1 px increments) and stores the counts in an accumulator matrix of angle vs distance. The size of the accumulator is 180x(diagonal/2). Next it searches this space for peaks in counts and converts the locations of the peaks to slope and intercept in the normal x,y input image space. Use the slope/intercepts to find the endpoints clipped to the bounds of the image. The lines are then drawn. The counts are a measure of the length of the lines</p> 171 172<p>The format of the HoughLineImage method is:</p> 173 174<pre class="text"> 175Image *HoughLineImage(const Image *image,const size_t width, 176 const size_t height,const size_t threshold,ExceptionInfo *exception) 177</pre> 178 179<p>A description of each parameter follows:</p> 180 181<dd> 182</dd> 183 184<dd> </dd> 185<dl class="dl-horizontal"> 186<dt>image</dt> 187<dd>the image. </dd> 188 189<dd> </dd> 190<dt>width, height</dt> 191<dd>find line pairs as local maxima in this neighborhood. </dd> 192 193<dd> </dd> 194<dt>threshold</dt> 195<dd>the line count threshold. </dd> 196 197<dd> </dd> 198<dt>exception</dt> 199<dd>return any errors or warnings in this structure. </dd> 200 201<dd> </dd> 202</dl> 203<h2><a href="../../api/MagickCore/feature_8c.html" id="MeanShiftImage">MeanShiftImage</a></h2> 204 205<p>MeanShiftImage() delineate arbitrarily shaped clusters in the image. For each pixel, it visits all the pixels in the neighborhood specified by the window centered at the pixel and excludes those that are outside the radius=(window-1)/2 surrounding the pixel. From those pixels, it finds those that are within the specified color distance from the current mean, and computes a new x,y centroid from those coordinates and a new mean. This new x,y centroid is used as the center for a new window. This process iterates until it converges and the final mean is replaces the (original window center) pixel value. It repeats this process for the next pixel, etc., until it processes all pixels in the image. Results are typically better with colorspaces other than sRGB. We recommend YIQ, YUV or YCbCr.</p> 206 207<p>The format of the MeanShiftImage method is:</p> 208 209<pre class="text"> 210Image *MeanShiftImage(const Image *image,const size_t width, 211 const size_t height,const double color_distance, 212 ExceptionInfo *exception) 213</pre> 214 215<p>A description of each parameter follows:</p> 216 217<dd> 218</dd> 219 220<dd> </dd> 221<dl class="dl-horizontal"> 222<dt>image</dt> 223<dd>the image. </dd> 224 225<dd> </dd> 226<dt>width, height</dt> 227<dd>find pixels in this neighborhood. </dd> 228 229<dd> </dd> 230<dt>color_distance</dt> 231<dd>the color distance. </dd> 232 233<dd> </dd> 234<dt>exception</dt> 235<dd>return any errors or warnings in this structure. </dd> 236 237<dd> </dd> 238</dl> 239</div> 240 </div> 241 </main><!-- /.container --> 242 <footer class="magick-footer"> 243 <p><a href="../../www/security-policy.html">Security</a> • 244 <a href="../../www/architecture.html">Architecture</a> • 245 <a href="../../www/links.html">Related</a> • 246 <a href="../../www/sitemap.html">Sitemap</a> 247 248 <a href="feature.html#"><img class="d-inline" id="wand" alt="And Now a Touch of Magick" width="16" height="16" src="../../images/wand.ico"/></a> 249 250 <a href="http://pgp.mit.edu/pks/lookup?op=get&search=0x89AB63D48277377A">Public Key</a> • 251 <a href="../../www/support.html">Donate</a> • 252 <a href="../../www/contact.html">Contact Us</a> 253 <br/> 254 <small>© 1999-2019 ImageMagick Studio LLC</small></p> 255 </footer> 256 257 <!-- Javascript assets --> 258 <script src="../assets/magick.js" crossorigin="anonymous"></script> 259 <script>window.jQuery || document.write('<script src="https://localhost/ajax/libs/jquery/3.3.1/jquery.min.js"><\/script>')</script> 260</body> 261</html> 262<!-- Magick Cache 4th January 2019 05:48 -->
