first released version v6.0

.gitignore

+temporary/*
+*.class
+
+# eclipse specific git ignore
+*.pydevproject
+.project
+.metadata
+bin/**
+tmp/**
+tmp/**/*
+*.tmp
+*.bak
+*.swp
+*~.nib
+local.properties
+.classpath
+.settings/
+.loadpath
+*.hprof

.svn/entries

+12
\ No newline at end of file

.svn/format

+12
\ No newline at end of file

.svn/pristine/00/002a6f976c2a8515b86770e921479c2f3a156042.svn-base

+package jsl.segmentation;
+
+import image.Image;
+import image.IntegerImage;
+import image.algorithms.Algorithm;
+import image.algorithms.AlgorithmException;
+
+import java.awt.Point;
+import java.util.Stack;
+
+import jsl.io.ImageData;
+import jsl.utils.Progressable;
+
+/**
+ * Interface pour les algorithmes de segmentation. Un segmenteur doit surcharger au choix : -
+ * buildSegmentation(RawImage image) - buildSegmentation(fr.unistra.pelican.Image image) Par contre
+ * en fait pour l'instant il faut de toute facon surcharger
+ * buildSegmentation(fr.unistra.pelican.Image image) cf le
+ * @author derivaux
+ */
+public abstract class Segmenteur implements Cloneable, Progressable {
+	/** Parametres de la methode de segmentation */
+	public Parametres	paramSegmenteur;
+
+	/** IO Image */
+	public ImageData	image;
+
+	/** Resultat segmenteur */
+	public Resultat	  resultatSegmenteur;
+
+	/**
+	 * Parametre de progression pour l'affichage de la barre de progression
+	 */
+	public int	      progress	= 0;
+
+	/**
+	 * Valeur maximale de la progression
+	 */
+	public int	      progressM	= 100;
+
+	/**
+	 * Constructeur par defaut
+	 */
+	public Segmenteur() {}
+
+	/**
+	 * Constructeur avec passage de paramétres
+	 * @param resultatSegmenteur
+	 */
+	public Segmenteur(Parametres params, ImageData image, Resultat resultat) {
+		super();
+		this.paramSegmenteur = params;
+		this.image = image;
+		this.resultatSegmenteur = resultat;
+	}
+
+	abstract protected void build(Image image);
+
+	abstract public Segmenteur copy();
+
+	/**
+	 * @param image Pelican Initial avant le processus de segmenteur
+	 */
+	final public void run() {
+		this.progressM = 2;
+		this.build(this.image.imageBrutePiaf);
+		this.incProgress();
+		this.endProgress();
+	}
+
+	public void setResultatImage(Image imageLabels) {
+		this.resultatSegmenteur.setLabelsPiaf(imageLabels);
+	}
+
+	public int getNiveaux() {
+		return 1;
+	}
+
+	/**
+	 * get nom segmenteur
+	 */
+	abstract public String getNomSegmenteur();
+
+	/*
+	 * ================================================================================= GETERS and
+	 * SETers
+	 */
+	@Override
+	public Object clone() throws CloneNotSupportedException {
+		return this.copy();
+	}
+
+	@Override
+	public void endProgress() {
+		this.progress = this.progressM;
+	}
+
+	@Override
+	public int getProgress() {
+		return (int) (((double) this.progress / (double) this.progressM) * 100.0);
+	}
+
+	@Override
+	public void incProgress() {
+		this.progress++;
+	}
+
+	@Override
+	public void resetProgress() {
+		this.progress = 0;
+	}
+
+	@Override
+	public void setProgress(int value) {
+		this.progressM = value;
+	}
+
+	public Resultat getResultatSegmenteur() {
+		return resultatSegmenteur;
+	}
+
+	public void setResultatSegmenteur(Resultat resultatSegmenteur) {
+		this.resultatSegmenteur = resultatSegmenteur;
+	}
+
+	public Parametres getParamSegmenteur() {
+		return paramSegmenteur;
+	}
+
+	public void setParamSegmenteur(Parametres paramSegmenteur) {
+		this.paramSegmenteur = paramSegmenteur;
+	}
+
+	/**
+	 * Create a segment for each "composantes connexe". Use 8-connexity. Use equality for pixels on
+	 * integer level.
+	 */
+	public class SegmentByConnexity extends Algorithm {
+
+		public Image exec(Image image) {
+			return (Image) new SegmentByConnexity().process(image);
+		}
+
+		// Inputs parameters
+		public Image		inputImage;
+
+		// Outputs parameters
+		public IntegerImage	outputImage;
+
+		/**
+		 * Constructor
+		 */
+		public SegmentByConnexity() {
+
+			super();
+			super.inputs = "inputImage";
+			super.outputs = "outputImage";
+			super.help = "Segment image by 8-connexity.\n" + "Image inputImage\n" + "\n" + "Image outputImage\n" + "\n" + "";
+		}
+
+		private boolean areEquals(int x1, int y1, int x2, int y2) {
+			for (int b = 0; b < inputImage.getBDim(); b++)
+				if (inputImage.getPixelXYBInt(x1, y1, b) != inputImage.getPixelXYBInt(x2, y2, b))
+					return false;
+			return true;
+		}
+
+		/*
+		 * (non-Javadoc)
+		 * @see fr.unistra.pelican.Algorithm#launch()
+		 */
+		@Override
+		public void launch() throws AlgorithmException {
+			outputImage = new IntegerImage(inputImage.getXDim(), inputImage.getYDim(), 1, 1, 1);
+			outputImage.fill(-1);
+			int xDim = outputImage.getXDim();
+			int yDim = outputImage.getYDim();
+			int bDim = inputImage.getBDim();
+
+			int label = 0;
+
+			for (int x = 0; x < xDim; x++)
+				for (int y = 0; y < yDim; y++)
+					if (outputImage.getPixelXYInt(x, y) == -1)
+						newSegment(x, y, label++);
+			outputImage.setProperty("nbRegions", label);
+
+		}
+
+		private void newSegment(int x, int y, int label) {
+			outputImage.setPixelXYInt(x, y, label);
+
+			Stack<Point> fifo = new Stack<Point>();
+			fifo.push(new Point(x, y));
+
+			while (!fifo.empty()) {
+				Point p = fifo.pop();
+				outputImage.setPixelXYInt(p.x, p.y, label);
+
+				// For every pixel in the 8-neighbourhood of the pixel
+				for (int l = p.y - 1; l <= p.y + 1; l++) {
+					for (int k = p.x - 1; k <= p.x + 1; k++) {
+						if (k < 0 || k >= inputImage.getXDim() || l < 0 || l >= inputImage.getYDim())
+							continue;
+						if (!(k == p.x && l == p.y)) {
+							if (outputImage.getPixelXYInt(k, l) == -1 && areEquals(p.x, p.y, k, l))
+								fifo.push(new Point(k, l));
+						}
+					}
+				}
+			}
+		}
+
+	}
+}

.svn/pristine/04/041f6105d856c0a8688db66cffa7e529d49977c6.svn-base

+package jsl.segmentation.methodes.hierarchicalBinaryPartitionTree.utils;
+
+import image.Image;
+import image.IntegerImage;
+
+import java.awt.Point;
+import java.util.*;
+
+/**
+ * Create a segment for each "composantes connexe". Use 8-connexity. Use equality for pixels on
+ * integer level.
+ */
+public class SegmentByConnexityPelicanInteger {
+
+	// Inputs parameters
+	public Image	                            inputImagePelican;
+	public HashMap<Integer, ArrayList<Integer>>	inputRegion;
+
+	public int	                                xDim;
+	public int	                                yDim;
+	public int	                                bDim;
+
+	// Outputs parameters
+	public IntegerImage	                        outputImage;
+	HashMap<Integer, Integer>	                output	= new HashMap<Integer, Integer>();
+
+	/**
+	 * Constructor
+	 */
+	public SegmentByConnexityPelicanInteger(Image src) {
+		this.inputImagePelican = src;
+		xDim = this.inputImagePelican.xdim;
+		yDim = this.inputImagePelican.ydim;
+		bDim = this.inputImagePelican.bdim;
+	}
+
+	public SegmentByConnexityPelicanInteger(HashMap<Integer, ArrayList<Integer>> regionToSegment, int XDim, int YDim, int BDim) {
+		this.inputRegion = regionToSegment;
+		xDim = XDim;
+		yDim = YDim;
+		bDim = BDim;
+	}
+
+	public Image runForFullImage() {
+		outputImage = new IntegerImage(inputImagePelican.xdim, inputImagePelican.ydim, 1, 1, 1);
+
+		outputImage.fill(-1);
+
+		int label = 0;
+		for (int x = 0; x < xDim; x++)
+			for (int y = 0; y < yDim; y++)
+				if (outputImage.getPixelXYInt(x, y) == -1)
+					newSegmentForFullImage(x, y, label++);
+
+		outputImage.setProperty("nbRegions", label);
+		return outputImage;
+	}
+
+	public HashMap<Integer, Integer> runForRegions() {
+
+		for (int p : inputRegion.keySet()) {
+			output.put(p, -1);
+		}
+
+		int label = 0;
+		for (int p : inputRegion.keySet()) {
+			int x = p % xDim;
+			int y = p / xDim;
+
+			if (output.get(p) == -1) {
+				newSegmentForRegions(x, y, label++);
+			}
+		}
+		return output;
+	}
+
+	private void newSegmentForFullImage(int x, int y, int label) {
+		outputImage.setPixelXYInt(x, y, label);
+
+		Stack<Point> fifo = new Stack<Point>();
+		fifo.push(new Point(x, y));
+
+		while (!fifo.empty()) {
+			Point p = fifo.pop();
+			outputImage.setPixelXYInt(p.x, p.y, label);
+
+			// For every pixel in the 8-neighbourhood of the pixel
+			for (int l = p.y - 1; l <= p.y + 1; l++) {
+				for (int k = p.x - 1; k <= p.x + 1; k++) {
+					if (k < 0 || k >= xDim || l < 0 || l >= yDim)
+						continue;
+
+					if (!(k == p.x && l == p.y)) {
+
+						if (outputImage.getPixelXYInt(k, l) == -1 && areEqualsForFullImage(p.x, p.y, k, l)) {
+							fifo.push(new Point(k, l));
+						}
+					}
+				}
+			}
+		}
+	}
+
+	private void newSegmentForRegions(int x, int y, int label) {
+		output.put((y * xDim) + x, label);
+
+		Stack<Point> fifo = new Stack<Point>();
+		fifo.push(new Point(x, y));
+
+		while (!fifo.empty()) {
+			Point p = fifo.pop();
+			output.put(p.y * xDim + p.x, label);
+
+			// For every pixel in the 8-neighbourhood of the pixel
+			for (int l = p.y - 1; l <= p.y + 1; l++) {
+				for (int k = p.x - 1; k <= p.x + 1; k++) {
+					if (k < 0 || k >= xDim || l < 0 || l >= yDim)
+						continue;
+
+					if (!(k == p.x && l == p.y) && inputRegion.containsKey(l * (xDim) + k)) {
+						if (output.get(l * (xDim) + k) == -1 && areEqualsRegion(p.x, p.y, k, l)) {
+							fifo.push(new Point(k, l));
+						}
+					}
+				}
+			}
+		}
+	}
+
+	private boolean areEqualsForFullImage(int x1, int y1, int x2, int y2) {
+		for (int b = 0; b < bDim; b++)
+			if (inputImagePelican.getPixelXYBInt(x1, y1, b) != inputImagePelican.getPixelXYBInt(x2, y2, b))
+				return false;
+
+		return true;
+	}
+
+	private boolean areEqualsRegion(int x1, int y1, int x2, int y2) {
+		int p1 = y1 * xDim + x1;
+		int p2 = y2 * xDim + x2;
+
+		for (int b = 0; b < bDim; b++) {
+			if (inputRegion.get(p1).get(b).intValue() != inputRegion.get(p2).get(b).intValue()) {
+				return false;
+			}
+		}
+		return true;
+	}
+
+}

.svn/pristine/08/08ba55641d26ea5e3638954dd6945a4e6ec54775.svn-base

+package image.algorithms.morphology.gray;
+
+import image.BooleanImage;
+import image.Image;
+import image.algorithms.Algorithm;
+import image.utils.Point4D;
+
+/**
+ * This class performs a gray erosion with a 2-D flat structuring element
+ * 
+ * @author
+ */
+public class GrayErosion extends Algorithm {
+
+	/**
+	 * The input image
+	 */
+	public Image inputImage;
+
+	/**
+	 * The flat structuring element used in the morphological operation
+	 */
+	public BooleanImage se;
+
+	/**
+	 * The output image
+	 */
+	public Image outputImage;
+
+	/**
+	 * Default constructor
+	 */
+	public GrayErosion() {
+		super.inputs = "inputImage,se";
+		super.outputs = "outputImage";
+	}
+
+	/**
+	 * Performs a gray erosion with a 2-D flat structuring element
+	 * 
+	 * @param image
+	 *          The input image
+	 * @param se
+	 *          The flat structuring element used in the morphological operation
+	 * @return The output image
+	 */
+	public static Image exec(Image inputImage, BooleanImage se) {
+		return (Image) new GrayErosion().process(inputImage, se);
+	}
+	
+	/**
+	 * Performs a gray erosion with a 2-D flat structuring element and a mask
+	 * 
+	 * @param image
+	 *          The input image
+	 * @param se
+	 *          The flat structuring element used in the morphological operation
+	 * @param mask
+	 * 			Mask used to compute a part of the image         
+	 *          
+	 * @return The output image
+	 */
+	public static Image exec(Image inputImage, BooleanImage se, Image mask) {
+		return (Image) new GrayErosion().process(inputImage, se, mask);
+	}
+
+	/*
+	 * (non-Javadoc)
+	 * 
+	 * @see fr.unistra.pelican.Algorithm#launch()
+	 */
+	public void launch() {
+		outputImage = inputImage.copyImage(false);
+		int xDim = inputImage.getXDim();
+		int yDim = inputImage.getYDim();
+		int tDim = inputImage.getTDim();
+		int bDim = inputImage.getBDim();
+		int zDim = inputImage.getZDim();
+		Point4D[] points = se.foreground();
+		boolean isHere;
+		for ( int b = 0 ; b < bDim ; b++ )
+		for ( int t = 0 ; t < tDim ; t++ )
+		for ( int z = 0 ; z < zDim ; z++ )
+		for ( int y = 0 ; y < yDim ; y++ ) 
+		for ( int x = 0 ; x < xDim ; x++ ) { 
+
+			isHere = this.inputImage.isPresent( x,y,z,t,b );
+			if  ( !isHere ) outputImage.setPixelDouble( x,y,z,t,b, 0 );
+			else outputImage.setPixelDouble( x,y,z,t,b, getMinGray( x,y,z,t,b, points) );
+		}
+	}
+
+	/*
+	 * Return the min value under a flat structuring element.
+	 */
+	private double getMinGray(int x, int y, int z, int t, int b, Point4D[] points) {
+		double min = Double.MAX_VALUE;
+		boolean flag = false;
+		for (int i = 0; i < points.length; i++) {
+			int valX = x - se.getCenter().x + points[i].x;
+			int valY = y - se.getCenter().y + points[i].y;
+			int valZ = z - se.getCenter().z + points[i].z;
+			int valT = t - se.getCenter().t + points[i].t;
+			if (	valX >= 0 && valX < inputImage.getXDim() 
+					 && valY >= 0 && valY < inputImage.getYDim() 
+					 && valZ >= 0 && valZ < inputImage.getZDim() 
+					 && valT >= 0 && valT < inputImage.getTDim() 
+					 && inputImage.isPresent( valX,valY,valZ,valT,b ) ) { 
+
+				double value = inputImage.getPixelDouble(valX, valY, valZ, valT, b);
+				if (min > value)
+					min = value;
+				flag = true;
+			}
+		}
+		// FIXME: Strange, if nothing is under the se, what is the right way?
+		return (flag == true) ? min : inputImage.getPixelDouble(x, y, z, t, b);
+	}
+
+}

.svn/pristine/0d/0df410e0fc2b61b6e747d2e88d01a45f9b0c0417.svn-base

+package jsl.segmentation.methodes.regionmerging.utilsregionmerging.adjacenceutils;
+
+/**
+ * represente une demi adjacence une region possède une demi adjacences avec
+ * chacun de ses voisins
+ * 
+ * Pour chaque voisin on doit stocker son numéro de région et la fitness entre
+ * la région courante et ce voisin
+ *