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<div class="subTitle">org.opencv.imgproc</div>
<h2 title="Class IntelligentScissorsMB" class="title">Class IntelligentScissorsMB</h2>
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<li>java.lang.Object</li>
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<pre>public class <span class="typeNameLabel">IntelligentScissorsMB</span>
extends java.lang.Object</pre>
<div class="block">Intelligent Scissors image segmentation

 This class is used to find the path (contour) between two points
 which can be used for image segmentation.

 Usage example:
 SNIPPET: snippets/imgproc_segmentation.cpp usage_example_intelligent_scissors

 Reference: &lt;a href="http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.138.3811&amp;rep=rep1&amp;type=pdf"&gt;"Intelligent Scissors for Image Composition"&lt;/a&gt;
 algorithm designed by Eric N. Mortensen and William A. Barrett, Brigham Young University
 CITE: Mortensen95intelligentscissors</div>
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<td class="colOne"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#IntelligentScissorsMB--">IntelligentScissorsMB</a></span>()</code>&nbsp;</td>
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<td class="colFirst"><code>static <a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#Z:Z__fromPtr__-long-">__fromPtr__</a></span>(long&nbsp;addr)</code>&nbsp;</td>
</tr>
<tr id="i1" class="rowColor">
<td class="colFirst"><code><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#applyImage-org.opencv.core.Mat-">applyImage</a></span>(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;image)</code>
<div class="block">Specify input image and extract image features</div>
</td>
</tr>
<tr id="i2" class="altColor">
<td class="colFirst"><code><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#applyImageFeatures-org.opencv.core.Mat-org.opencv.core.Mat-org.opencv.core.Mat-">applyImageFeatures</a></span>(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;non_edge,
                  <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;gradient_direction,
                  <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;gradient_magnitude)</code>
<div class="block">Specify custom features of input image

 Customized advanced variant of applyImage() call.</div>
</td>
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<tr id="i3" class="rowColor">
<td class="colFirst"><code><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#applyImageFeatures-org.opencv.core.Mat-org.opencv.core.Mat-org.opencv.core.Mat-org.opencv.core.Mat-">applyImageFeatures</a></span>(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;non_edge,
                  <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;gradient_direction,
                  <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;gradient_magnitude,
                  <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;image)</code>
<div class="block">Specify custom features of input image

 Customized advanced variant of applyImage() call.</div>
</td>
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<tr id="i4" class="altColor">
<td class="colFirst"><code>void</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#buildMap-org.opencv.core.Point-">buildMap</a></span>(<a href="../../../org/opencv/core/Point.html" title="class in org.opencv.core">Point</a>&nbsp;sourcePt)</code>
<div class="block">Prepares a map of optimal paths for the given source point on the image

 <b>Note:</b> applyImage() / applyImageFeatures() must be called before this call</div>
</td>
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<tr id="i5" class="rowColor">
<td class="colFirst"><code>void</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#getContour-org.opencv.core.Point-org.opencv.core.Mat-">getContour</a></span>(<a href="../../../org/opencv/core/Point.html" title="class in org.opencv.core">Point</a>&nbsp;targetPt,
          <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;contour)</code>
<div class="block">Extracts optimal contour for the given target point on the image

 <b>Note:</b> buildMap() must be called before this call</div>
</td>
</tr>
<tr id="i6" class="altColor">
<td class="colFirst"><code>void</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#getContour-org.opencv.core.Point-org.opencv.core.Mat-boolean-">getContour</a></span>(<a href="../../../org/opencv/core/Point.html" title="class in org.opencv.core">Point</a>&nbsp;targetPt,
          <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;contour,
          boolean&nbsp;backward)</code>
<div class="block">Extracts optimal contour for the given target point on the image

 <b>Note:</b> buildMap() must be called before this call</div>
</td>
</tr>
<tr id="i7" class="rowColor">
<td class="colFirst"><code>long</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#getNativeObjAddr--">getNativeObjAddr</a></span>()</code>&nbsp;</td>
</tr>
<tr id="i8" class="altColor">
<td class="colFirst"><code><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#setEdgeFeatureCannyParameters-double-double-">setEdgeFeatureCannyParameters</a></span>(double&nbsp;threshold1,
                             double&nbsp;threshold2)</code>
<div class="block">Switch edge feature extractor to use Canny edge detector

 <b>Note:</b> "Laplacian Zero-Crossing" feature extractor is used by default (following to original article)

 SEE: Canny</div>
</td>
</tr>
<tr id="i9" class="rowColor">
<td class="colFirst"><code><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#setEdgeFeatureCannyParameters-double-double-int-">setEdgeFeatureCannyParameters</a></span>(double&nbsp;threshold1,
                             double&nbsp;threshold2,
                             int&nbsp;apertureSize)</code>
<div class="block">Switch edge feature extractor to use Canny edge detector

 <b>Note:</b> "Laplacian Zero-Crossing" feature extractor is used by default (following to original article)

 SEE: Canny</div>
</td>
</tr>
<tr id="i10" class="altColor">
<td class="colFirst"><code><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#setEdgeFeatureCannyParameters-double-double-int-boolean-">setEdgeFeatureCannyParameters</a></span>(double&nbsp;threshold1,
                             double&nbsp;threshold2,
                             int&nbsp;apertureSize,
                             boolean&nbsp;L2gradient)</code>
<div class="block">Switch edge feature extractor to use Canny edge detector

 <b>Note:</b> "Laplacian Zero-Crossing" feature extractor is used by default (following to original article)

 SEE: Canny</div>
</td>
</tr>
<tr id="i11" class="rowColor">
<td class="colFirst"><code><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#setEdgeFeatureZeroCrossingParameters--">setEdgeFeatureZeroCrossingParameters</a></span>()</code>
<div class="block">Switch to "Laplacian Zero-Crossing" edge feature extractor and specify its parameters

 This feature extractor is used by default according to article.</div>
</td>
</tr>
<tr id="i12" class="altColor">
<td class="colFirst"><code><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#setEdgeFeatureZeroCrossingParameters-float-">setEdgeFeatureZeroCrossingParameters</a></span>(float&nbsp;gradient_magnitude_min_value)</code>
<div class="block">Switch to "Laplacian Zero-Crossing" edge feature extractor and specify its parameters

 This feature extractor is used by default according to article.</div>
</td>
</tr>
<tr id="i13" class="rowColor">
<td class="colFirst"><code><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#setGradientMagnitudeMaxLimit--">setGradientMagnitudeMaxLimit</a></span>()</code>
<div class="block">Specify gradient magnitude max value threshold

 Zero limit value is used to disable gradient magnitude thresholding (default behavior, as described in original article).</div>
</td>
</tr>
<tr id="i14" class="altColor">
<td class="colFirst"><code><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#setGradientMagnitudeMaxLimit-float-">setGradientMagnitudeMaxLimit</a></span>(float&nbsp;gradient_magnitude_threshold_max)</code>
<div class="block">Specify gradient magnitude max value threshold

 Zero limit value is used to disable gradient magnitude thresholding (default behavior, as described in original article).</div>
</td>
</tr>
<tr id="i15" class="rowColor">
<td class="colFirst"><code><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html#setWeights-float-float-float-">setWeights</a></span>(float&nbsp;weight_non_edge,
          float&nbsp;weight_gradient_direction,
          float&nbsp;weight_gradient_magnitude)</code>
<div class="block">Specify weights of feature functions

 Consider keeping weights normalized (sum of weights equals to 1.0)
 Discrete dynamic programming (DP) goal is minimization of costs between pixels.</div>
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<h4>IntelligentScissorsMB</h4>
<pre>public&nbsp;IntelligentScissorsMB()</pre>
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<pre>public static&nbsp;<a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a>&nbsp;__fromPtr__(long&nbsp;addr)</pre>
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<pre>public&nbsp;<a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a>&nbsp;applyImage(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;image)</pre>
<div class="block">Specify input image and extract image features</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>image</code> - input image. Type is #CV_8UC1 / #CV_8UC3</dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
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<pre>public&nbsp;<a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a>&nbsp;applyImageFeatures(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;non_edge,
                                                <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;gradient_direction,
                                                <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;gradient_magnitude)</pre>
<div class="block">Specify custom features of input image

 Customized advanced variant of applyImage() call.</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>non_edge</code> - Specify cost of non-edge pixels. Type is CV_8UC1. Expected values are <code>{0, 1}</code>.</dd>
<dd><code>gradient_direction</code> - Specify gradient direction feature. Type is CV_32FC2. Values are expected to be normalized: <code>x^2 + y^2 == 1</code></dd>
<dd><code>gradient_magnitude</code> - Specify cost of gradient magnitude function: Type is CV_32FC1. Values should be in range <code>[0, 1]</code>.</dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
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<h4>applyImageFeatures</h4>
<pre>public&nbsp;<a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a>&nbsp;applyImageFeatures(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;non_edge,
                                                <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;gradient_direction,
                                                <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;gradient_magnitude,
                                                <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;image)</pre>
<div class="block">Specify custom features of input image

 Customized advanced variant of applyImage() call.</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>non_edge</code> - Specify cost of non-edge pixels. Type is CV_8UC1. Expected values are <code>{0, 1}</code>.</dd>
<dd><code>gradient_direction</code> - Specify gradient direction feature. Type is CV_32FC2. Values are expected to be normalized: <code>x^2 + y^2 == 1</code></dd>
<dd><code>gradient_magnitude</code> - Specify cost of gradient magnitude function: Type is CV_32FC1. Values should be in range <code>[0, 1]</code>.</dd>
<dd><code>image</code> - <b>Optional parameter</b>. Must be specified if subset of features is specified (non-specified features are calculated internally)</dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
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<h4>buildMap</h4>
<pre>public&nbsp;void&nbsp;buildMap(<a href="../../../org/opencv/core/Point.html" title="class in org.opencv.core">Point</a>&nbsp;sourcePt)</pre>
<div class="block">Prepares a map of optimal paths for the given source point on the image

 <b>Note:</b> applyImage() / applyImageFeatures() must be called before this call</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>sourcePt</code> - The source point used to find the paths</dd>
</dl>
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<h4>getContour</h4>
<pre>public&nbsp;void&nbsp;getContour(<a href="../../../org/opencv/core/Point.html" title="class in org.opencv.core">Point</a>&nbsp;targetPt,
                       <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;contour)</pre>
<div class="block">Extracts optimal contour for the given target point on the image

 <b>Note:</b> buildMap() must be called before this call</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>targetPt</code> - The target point</dd>
<dd><code>contour</code> - The list of pixels which contains optimal path between the source and the target points of the image. Type is CV_32SC2 (compatible with <code>std::vector&amp;lt;Point&amp;gt;</code>)</dd>
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<h4>getContour</h4>
<pre>public&nbsp;void&nbsp;getContour(<a href="../../../org/opencv/core/Point.html" title="class in org.opencv.core">Point</a>&nbsp;targetPt,
                       <a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a>&nbsp;contour,
                       boolean&nbsp;backward)</pre>
<div class="block">Extracts optimal contour for the given target point on the image

 <b>Note:</b> buildMap() must be called before this call</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>targetPt</code> - The target point</dd>
<dd><code>contour</code> - The list of pixels which contains optimal path between the source and the target points of the image. Type is CV_32SC2 (compatible with <code>std::vector&amp;lt;Point&amp;gt;</code>)</dd>
<dd><code>backward</code> - Flag to indicate reverse order of retrived pixels (use "true" value to fetch points from the target to the source point)</dd>
</dl>
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<h4>getNativeObjAddr</h4>
<pre>public&nbsp;long&nbsp;getNativeObjAddr()</pre>
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<h4>setEdgeFeatureCannyParameters</h4>
<pre>public&nbsp;<a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a>&nbsp;setEdgeFeatureCannyParameters(double&nbsp;threshold1,
                                                           double&nbsp;threshold2)</pre>
<div class="block">Switch edge feature extractor to use Canny edge detector

 <b>Note:</b> "Laplacian Zero-Crossing" feature extractor is used by default (following to original article)

 SEE: Canny</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>threshold1</code> - automatically generated</dd>
<dd><code>threshold2</code> - automatically generated</dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
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<h4>setEdgeFeatureCannyParameters</h4>
<pre>public&nbsp;<a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a>&nbsp;setEdgeFeatureCannyParameters(double&nbsp;threshold1,
                                                           double&nbsp;threshold2,
                                                           int&nbsp;apertureSize)</pre>
<div class="block">Switch edge feature extractor to use Canny edge detector

 <b>Note:</b> "Laplacian Zero-Crossing" feature extractor is used by default (following to original article)

 SEE: Canny</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>threshold1</code> - automatically generated</dd>
<dd><code>threshold2</code> - automatically generated</dd>
<dd><code>apertureSize</code> - automatically generated</dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
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<h4>setEdgeFeatureCannyParameters</h4>
<pre>public&nbsp;<a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a>&nbsp;setEdgeFeatureCannyParameters(double&nbsp;threshold1,
                                                           double&nbsp;threshold2,
                                                           int&nbsp;apertureSize,
                                                           boolean&nbsp;L2gradient)</pre>
<div class="block">Switch edge feature extractor to use Canny edge detector

 <b>Note:</b> "Laplacian Zero-Crossing" feature extractor is used by default (following to original article)

 SEE: Canny</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>threshold1</code> - automatically generated</dd>
<dd><code>threshold2</code> - automatically generated</dd>
<dd><code>apertureSize</code> - automatically generated</dd>
<dd><code>L2gradient</code> - automatically generated</dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
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<h4>setEdgeFeatureZeroCrossingParameters</h4>
<pre>public&nbsp;<a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a>&nbsp;setEdgeFeatureZeroCrossingParameters()</pre>
<div class="block">Switch to "Laplacian Zero-Crossing" edge feature extractor and specify its parameters

 This feature extractor is used by default according to article.

 Implementation has additional filtering for regions with low-amplitude noise.
 This filtering is enabled through parameter of minimal gradient amplitude (use some small value 4, 8, 16).

 <b>Note:</b> Current implementation of this feature extractor is based on processing of grayscale images (color image is converted to grayscale image first).

 <b>Note:</b> Canny edge detector is a bit slower, but provides better results (especially on color images): use setEdgeFeatureCannyParameters().</div>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
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<h4>setEdgeFeatureZeroCrossingParameters</h4>
<pre>public&nbsp;<a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a>&nbsp;setEdgeFeatureZeroCrossingParameters(float&nbsp;gradient_magnitude_min_value)</pre>
<div class="block">Switch to "Laplacian Zero-Crossing" edge feature extractor and specify its parameters

 This feature extractor is used by default according to article.

 Implementation has additional filtering for regions with low-amplitude noise.
 This filtering is enabled through parameter of minimal gradient amplitude (use some small value 4, 8, 16).

 <b>Note:</b> Current implementation of this feature extractor is based on processing of grayscale images (color image is converted to grayscale image first).

 <b>Note:</b> Canny edge detector is a bit slower, but provides better results (especially on color images): use setEdgeFeatureCannyParameters().</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>gradient_magnitude_min_value</code> - Minimal gradient magnitude value for edge pixels (default: 0, check is disabled)</dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
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<h4>setGradientMagnitudeMaxLimit</h4>
<pre>public&nbsp;<a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a>&nbsp;setGradientMagnitudeMaxLimit()</pre>
<div class="block">Specify gradient magnitude max value threshold

 Zero limit value is used to disable gradient magnitude thresholding (default behavior, as described in original article).
 Otherwize pixels with <code>gradient magnitude &amp;gt;= threshold</code> have zero cost.

 <b>Note:</b> Thresholding should be used for images with irregular regions (to avoid stuck on parameters from high-contract areas, like embedded logos).</div>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
</li>
</ul>
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<h4>setGradientMagnitudeMaxLimit</h4>
<pre>public&nbsp;<a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a>&nbsp;setGradientMagnitudeMaxLimit(float&nbsp;gradient_magnitude_threshold_max)</pre>
<div class="block">Specify gradient magnitude max value threshold

 Zero limit value is used to disable gradient magnitude thresholding (default behavior, as described in original article).
 Otherwize pixels with <code>gradient magnitude &amp;gt;= threshold</code> have zero cost.

 <b>Note:</b> Thresholding should be used for images with irregular regions (to avoid stuck on parameters from high-contract areas, like embedded logos).</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>gradient_magnitude_threshold_max</code> - Specify gradient magnitude max value threshold (default: 0, disabled)</dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
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<h4>setWeights</h4>
<pre>public&nbsp;<a href="../../../org/opencv/imgproc/IntelligentScissorsMB.html" title="class in org.opencv.imgproc">IntelligentScissorsMB</a>&nbsp;setWeights(float&nbsp;weight_non_edge,
                                        float&nbsp;weight_gradient_direction,
                                        float&nbsp;weight_gradient_magnitude)</pre>
<div class="block">Specify weights of feature functions

 Consider keeping weights normalized (sum of weights equals to 1.0)
 Discrete dynamic programming (DP) goal is minimization of costs between pixels.</div>
<dl>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>weight_non_edge</code> - Specify cost of non-edge pixels (default: 0.43f)</dd>
<dd><code>weight_gradient_direction</code> - Specify cost of gradient direction function (default: 0.43f)</dd>
<dd><code>weight_gradient_magnitude</code> - Specify cost of gradient magnitude function (default: 0.14f)</dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>automatically generated</dd>
</dl>
</li>
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<p class="legalCopy"><small>Generated on 2023-06-28 12:47:21 / OpenCV 4.8.0</small></p>
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