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Add Hough circle transform and detector ops
The transform is: - 2D version only. - weigthed or not. The detectors retrieve the Hough circles from a vote image generated by a HoughCircleTransformOp. The circles are returned as a collection of HoughCircles. Two versions: - one with a DoG detector and sub-pixel accuracy. - one with plain local extrema. Signed-off-by: Curtis Rueden <[email protected]>
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‎pom.xml‎

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@@ -273,6 +273,11 @@
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<artifactId>scifio</artifactId>
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<scope>test</scope>
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</dependency>
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<dependency>
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<groupId>net.imagej</groupId>
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<artifactId>imagej-ui-swing</artifactId>
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<scope>test</scope>
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</dependency>
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<dependency>
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<!-- Do not remove - Maven incorrectly identifies it as an unused dependency! -->
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<groupId>org.scijava</groupId>

‎src/main/java/net/imagej/ops/segment/SegmentNamespace.java‎

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* %%
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
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*
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*
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* 1. Redistributions of source code must retain the above copyright notice,
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* this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
@@ -35,16 +35,23 @@
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import net.imagej.ops.Namespace;
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import net.imagej.ops.OpMethod;
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import net.imagej.ops.Ops;
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import net.imagej.ops.segment.hough.HoughCircle;
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import net.imglib2.IterableInterval;
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import net.imglib2.RandomAccessible;
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import net.imglib2.RandomAccessibleInterval;
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import net.imglib2.RealPoint;
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import net.imglib2.img.Img;
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import net.imglib2.roi.geom.real.WritablePolyline;
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import net.imglib2.type.BooleanType;
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import net.imglib2.type.NativeType;
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import net.imglib2.type.numeric.RealType;
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import net.imglib2.type.numeric.real.DoubleType;
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import org.scijava.plugin.Plugin;
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/**
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* The segment namespace contains segmentation operations.
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*
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*
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* @author Gabe Selzer
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*/
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@Plugin(type = Namespace.class)
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final int ridgeLengthMin)
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{
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@SuppressWarnings("unchecked")
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final List<? extends WritablePolyline> result = (List<? extends WritablePolyline>) ops().run(
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Ops.Segment.DetectRidges.class, input, width, lowerThreshold,
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higherThreshold, ridgeLengthMin);
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final List<? extends WritablePolyline> result =
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(List<? extends WritablePolyline>) ops().run(
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Ops.Segment.DetectRidges.class, input, width, lowerThreshold,
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higherThreshold, ridgeLengthMin);
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return result;
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}
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// -- detectJunctions --
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@OpMethod(op = net.imagej.ops.segment.detectJunctions.DefaultDetectJunctions.class)
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public List<RealPoint> detectJunctions(final List<? extends WritablePolyline> lines)
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@OpMethod(
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op = net.imagej.ops.segment.detectJunctions.DefaultDetectJunctions.class)
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public List<RealPoint> detectJunctions(
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final List<? extends WritablePolyline> lines)
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{
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@SuppressWarnings("unchecked")
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final List<RealPoint> result = (List<RealPoint>) ops().run(
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Ops.Segment.DetectJunctions.class, lines);
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return result;
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}
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@OpMethod(op = net.imagej.ops.segment.detectJunctions.DefaultDetectJunctions.class)
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public List<RealPoint> detectJunctions(final List<? extends WritablePolyline> lines,
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final double threshold)
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@OpMethod(
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op = net.imagej.ops.segment.detectJunctions.DefaultDetectJunctions.class)
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public List<RealPoint> detectJunctions(
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final List<? extends WritablePolyline> lines, final double threshold)
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{
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@SuppressWarnings("unchecked")
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final List<RealPoint> result = (List<RealPoint>) ops().run(
@@ -91,6 +102,137 @@ public List<RealPoint> detectJunctions(final List<? extends WritablePolyline> li
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return result;
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}
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// -- detectHoughCircleDoG --
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@OpMethod(op = net.imagej.ops.segment.hough.HoughCircleDetectorDogOp.class)
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public <T extends RealType<T> & NativeType<T>> List<HoughCircle>
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detectHoughCircleDoG(final RandomAccessibleInterval<T> in,
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final double circleThickness, final double minRadius,
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final double stepRadius, final double sigma)
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{
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@SuppressWarnings("unchecked")
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final List<HoughCircle> result = (List<HoughCircle>) ops().run(
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net.imagej.ops.Ops.Segment.DetectHoughCircleDoG.class, in,
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circleThickness, minRadius, stepRadius, sigma);
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return result;
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}
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@OpMethod(op = net.imagej.ops.segment.hough.HoughCircleDetectorDogOp.class)
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public <T extends RealType<T> & NativeType<T>> List<HoughCircle>
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detectHoughCircleDoG(final RandomAccessibleInterval<T> in,
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final double circleThickness, final double minRadius,
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final double stepRadius, final double sigma, final double sensitivity)
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{
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@SuppressWarnings("unchecked")
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final List<HoughCircle> result = (List<HoughCircle>) ops().run(
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net.imagej.ops.Ops.Segment.DetectHoughCircleDoG.class, in,
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circleThickness, minRadius, stepRadius, sigma, sensitivity);
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return result;
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}
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// -- detectHoughCircleLE --
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@OpMethod(
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op = net.imagej.ops.segment.hough.HoughCircleDetectorLocalExtremaOp.class)
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public <T extends RealType<T> & NativeType<T>> List<HoughCircle>
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detectHoughCircleLE(final RandomAccessibleInterval<T> in,
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final double minRadius, final double stepRadius)
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{
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@SuppressWarnings("unchecked")
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final List<HoughCircle> result = (List<HoughCircle>) ops().run(
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net.imagej.ops.Ops.Segment.DetectHoughCircleLE.class, in, minRadius,
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stepRadius);
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return result;
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}
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@OpMethod(
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op = net.imagej.ops.segment.hough.HoughCircleDetectorLocalExtremaOp.class)
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public <T extends RealType<T> & NativeType<T>> List<HoughCircle>
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detectHoughCircleLE(final RandomAccessibleInterval<T> in,
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final double minRadius, final double stepRadius, final double sensitivity)
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{
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@SuppressWarnings("unchecked")
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final List<HoughCircle> result = (List<HoughCircle>) ops().run(
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net.imagej.ops.Ops.Segment.DetectHoughCircleLE.class, in, minRadius,
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stepRadius, sensitivity);
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return result;
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}
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// -- transformHoughCircle --
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@OpMethod(op = net.imagej.ops.segment.hough.HoughTransformOpNoWeights.class)
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public <T extends BooleanType<T>> Img<DoubleType> transformHoughCircle(
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final IterableInterval<T> in, final long minRadius, final long maxRadius)
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{
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@SuppressWarnings("unchecked")
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final Img<DoubleType> result = (Img<DoubleType>) ops().run(
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net.imagej.ops.Ops.Segment.TransformHoughCircle.class, in, minRadius,
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maxRadius);
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return result;
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}
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@OpMethod(op = net.imagej.ops.segment.hough.HoughTransformOpNoWeights.class)
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public <T extends BooleanType<T>> Img<DoubleType> transformHoughCircle(
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final Img<DoubleType> out, final IterableInterval<T> in,
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final long minRadius, final long maxRadius)
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{
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@SuppressWarnings("unchecked")
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final Img<DoubleType> result = (Img<DoubleType>) ops().run(
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net.imagej.ops.Ops.Segment.TransformHoughCircle.class, out, in, minRadius,
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maxRadius);
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return result;
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}
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@OpMethod(op = net.imagej.ops.segment.hough.HoughTransformOpNoWeights.class)
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public <T extends BooleanType<T>> Img<DoubleType> transformHoughCircle(
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final Img<DoubleType> out, final IterableInterval<T> in,
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final long minRadius, final long maxRadius, final long stepRadius)
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{
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@SuppressWarnings("unchecked")
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final Img<DoubleType> result = (Img<DoubleType>) ops().run(
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net.imagej.ops.Ops.Segment.TransformHoughCircle.class, out, in, minRadius,
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maxRadius, stepRadius);
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return result;
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}
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@OpMethod(op = net.imagej.ops.segment.hough.HoughTransformOpWeights.class)
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public <T extends BooleanType<T>, R extends RealType<R>> Img<DoubleType>
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transformHoughCircle(final IterableInterval<T> in, final long minRadius,
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final long maxRadius, final RandomAccessible<R> weights)
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{
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@SuppressWarnings("unchecked")
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final Img<DoubleType> result = (Img<DoubleType>) ops().run(
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net.imagej.ops.Ops.Segment.TransformHoughCircle.class, in, minRadius,
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maxRadius, weights);
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return result;
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}
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@OpMethod(op = net.imagej.ops.segment.hough.HoughTransformOpWeights.class)
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public <T extends BooleanType<T>, R extends RealType<R>> Img<DoubleType>
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transformHoughCircle(final Img<DoubleType> out,
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final IterableInterval<T> in, final long minRadius, final long maxRadius,
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final RandomAccessible<R> weights)
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{
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@SuppressWarnings("unchecked")
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final Img<DoubleType> result = (Img<DoubleType>) ops().run(
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net.imagej.ops.Ops.Segment.TransformHoughCircle.class, out, in, minRadius,
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maxRadius, weights);
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return result;
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}
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@OpMethod(op = net.imagej.ops.segment.hough.HoughTransformOpWeights.class)
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public <T extends BooleanType<T>, R extends RealType<R>> Img<DoubleType>
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transformHoughCircle(final Img<DoubleType> out,
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final IterableInterval<T> in, final long minRadius, final long maxRadius,
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final long stepRadius, final RandomAccessible<R> weights)
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{
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@SuppressWarnings("unchecked")
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final Img<DoubleType> result = (Img<DoubleType>) ops().run(
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net.imagej.ops.Ops.Segment.TransformHoughCircle.class, out, in, minRadius,
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maxRadius, stepRadius, weights);
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return result;
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}
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// -- Namespace methods --
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@Override

‎src/main/java/net/imagej/ops/segment/hough/HoughCircle.java‎

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package net.imagej.ops.segment.hough;
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import net.imglib2.RealLocalizable;
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import net.imglib2.roi.geom.real.AbstractWritableSphere;
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/**
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* Representation of a circle segmented via Hough circle transformation.
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* <p>
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* Instances are {@link RealLocalizable} and have a radius (in pixel units) and
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* a sensitivity. The sensitivity factor is used to report a quality of the
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* Hough circle detection, the smallest the better the circle. The sensitivity
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* can be used to sort a list of circles.
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*
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* @author Jean-Yves Tinevez.
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* @author Gabe Selzer.
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*
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*/
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public class HoughCircle extends AbstractWritableSphere implements
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Comparable<HoughCircle>
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{
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private final double sensitivity;
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public HoughCircle( final RealLocalizable pos, final double radius, final double sensitivity )
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{
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super( getCenter(pos) , radius);
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this.radius = radius;
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this.sensitivity = sensitivity;
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}
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private static double[] getCenter(RealLocalizable l) {
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double[] center = new double[l.numDimensions()];
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l.localize(center);
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return center;
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}
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@Override
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public String toString()
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{
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final StringBuilder sb = new StringBuilder();
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char c = '(';
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for ( int i = 0; i < numDimensions(); i++ )
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{
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sb.append( c );
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sb.append( String.format( "%.1f", center[ i ] ) );
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c = ',';
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}
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sb.append( ")" );
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return String.format( "%s\tR=%.1f\tSensitivity=%.1f", sb.toString(), radius, sensitivity );
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}
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public double getRadius()
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{
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return radius;
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}
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public double getSensitivity()
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{
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return sensitivity;
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}
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@Override
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public int compareTo( final HoughCircle o )
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{
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return sensitivity < o.sensitivity ? -1 : sensitivity > o.sensitivity ? +1 : 0;
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}
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@Override
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public boolean test( final RealLocalizable point )
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{
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final double dx = center[0] - point.getDoublePosition( 0 );
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final double dy = center[1] - point.getDoublePosition( 1 );
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final double dr2 = dx * dx + dy * dy;
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if ( dr2 < radius * radius )
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return false;
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return true;
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}
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}

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