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ModularImageAnalysis (MIA) is an ImageJ plugin which provides a modular framework for assembling image and object analysis workflows. Detected objects can be transformed, filtered, measured and related. Analysis workflows are batch-enabled by default, allowing easy processing of high-content datasets.
/*
* "Concave" hulls by Glenn Hudson and Matt Duckham
*
* Source code downloaded from https://archive.md/l3Un5#selection-571.0-587.218 on 3rd November 2021.
*
* - This software is Copyright (C) 2008 Glenn Hudson released under Gnu Public License (GPL). Under
* GPL you are free to use, modify, and redistribute the software. Please acknowledge Glenn Hudson
* and Matt Duckham as the source of this software if you do use or adapt the code in further research
* or other work. For full details of GPL see http://www.gnu.org/licenses/gpl-3.0.txt.
* - This software comes with no warranty of any kind, expressed or implied.
*
* A paper with full details of the characteristic hulls algorithm is published in Pattern Recognition.
* Duckham, M., Kulik, L., Worboys, M.F., Galton, A. (2008) Efficient generation of simple polygons for
* characterizing the shape of a set of points in the plane. Pattern Recognition v41, 3224-3236
*
* The software was developed by Glenn Hudson while working with me as an RA. The characteristic shapes
* algorithm is collaborative work between Matt Duckham, Lars Kulik, Antony Galton, and Mike Worboys.
*
*/
package signalprocesser.voronoi.representation;
import java.util.ArrayList;
import signalprocesser.voronoi.VPoint;
import signalprocesser.voronoi.representation.boundaryproblem.BoundaryProblemRepresentation;
import signalprocesser.voronoi.representation.simpletriangulation.SimpleTriangulationRepresentation;
import signalprocesser.voronoi.representation.triangulation.TriangulationRepresentation;
import signalprocesser.voronoi.representation.voronoicell.VVoronoiCell;
import signalprocesser.voronoi.representation.voronoicell.VoronoiCellRepresentation;
public class RepresentationFactory {
// Don't allow to be instantiated
private RepresentationFactory() { }
/* ***************************************************** */
// Create Representation Methods
public static AbstractRepresentation createVoronoiCellRepresentation() {
return new VoronoiCellRepresentation();
}
public static AbstractRepresentation createTriangulationRepresentation() {
return new TriangulationRepresentation();
}
public static AbstractRepresentation createSimpleTriangulationRepresentation() {
return new SimpleTriangulationRepresentation();
}
public static AbstractRepresentation createBoundaryProblemRepresentation() {
return new BoundaryProblemRepresentation();
}
/* ***************************************************** */
// Conversion Methods
public static ArrayList convertPointsToVPoints(ArrayList points) {
ArrayList newarraylist = new ArrayList();
for ( VPoint point : points ) {
newarraylist.add( new VPoint(point) );
}
return newarraylist;
}
public static ArrayList convertPointsToVoronoiCellPoints(ArrayList points) {
ArrayList newarraylist = new ArrayList();
for ( VPoint point : points ) {
newarraylist.add( new VVoronoiCell(point) );
}
return newarraylist;
}
public static ArrayList convertPointsToTriangulationPoints(ArrayList points) {
signalprocesser.voronoi.representation.triangulation.VVertex.uniqueid = 1;
ArrayList newarraylist = new ArrayList();
for ( VPoint point : points ) {
newarraylist.add( new signalprocesser.voronoi.representation.triangulation.VVertex(point) );
}
return newarraylist;
}
public static ArrayList convertPointsToSimpleTriangulationPoints(ArrayList points) {
return convertPointsToVPoints( points );
}
public static ArrayList convertPointsToBoundaryProblemPoints(ArrayList points) {
ArrayList newarraylist = new ArrayList();
for ( VPoint point : points ) {
newarraylist.add( new signalprocesser.voronoi.representation.boundaryproblem.voronoicell.VVoronoiCell(point) );
}
return newarraylist;
}
/* ***************************************************** */
}