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package analyse;
import java.awt.Point;
import java.awt.image.BufferedImage;
import java.awt.image.ColorModel;
import java.awt.image.DataBuffer;
import java.awt.image.DataBufferInt;
import java.awt.image.Raster;
import java.awt.image.SampleModel;
import java.awt.image.renderable.ParameterBlock;
import javax.media.jai.Histogram;
import javax.media.jai.JAI;
import javax.media.jai.PlanarImage;
import javax.media.jai.RasterFactory;
import javax.media.jai.TiledImage;
/**
* Skeleton (v2)
*
* Original algorithm : Dr. Chai Quek
* Modified algorithm : Xavier Philippeau
*
* @author Xavier Philippeau (based on work of Dr. Chai Quek)
*
*/
public class Skeleton {
// Smoothing pattern
private byte[] pattern1={-1,1,0,1,0,0,0,0};
private byte[] pattern2={0,1,0,1,-1,0,0,0};
private byte[] pattern3={0,0,-1,1,0,1,0,0};
private byte[] pattern4={0,0,0,1,0,1,-1,0};
private byte[] pattern5={0,0,0,0,-1,1,0,1};
private byte[] pattern6={-1,0,0,0,0,1,0,1};
private byte[] pattern7={0,1,0,0,0,0,-1,1};
private byte[] pattern8={0,1,-1,0,0,0,0,1};
// Neighbourhood
private int neighbourhood(byte[][] c,int x,int y) {
int neighbourhood=0;
if (c[x-1][y-1]==1) neighbourhood++;
if (c[x-1][y ]==1) neighbourhood++;
if (c[x-1][y+1]==1) neighbourhood++;
if (c[x ][y+1]==1) neighbourhood++;
if (c[x+1][y+1]==1) neighbourhood++;
if (c[x+1][y ]==1) neighbourhood++;
if (c[x+1][y-1]==1) neighbourhood++;
if (c[x ][y-1]==1) neighbourhood++;
return neighbourhood;
}
// Transitions Count
private int transitions(byte[][] c,int x,int y) {
int transitions=0;
if (c[x-1][y-1]==0 && c[x-1][y ]==1) transitions++;
if (c[x-1][y ]==0 && c[x-1][y+1]==1) transitions++;
if (c[x-1][y+1]==0 && c[x ][y+1]==1) transitions++;
if (c[x ][y+1]==0 && c[x+1][y+1]==1) transitions++;
if (c[x+1][y+1]==0 && c[x+1][y ]==1) transitions++;
if (c[x+1][y ]==0 && c[x+1][y-1]==1) transitions++;
if (c[x+1][y-1]==0 && c[x ][y-1]==1) transitions++;
if (c[x ][y-1]==0 && c[x-1][y-1]==1) transitions++;
return transitions;
}
// Match a pattern
private boolean matchPattern(byte[][] c,int x,int y,byte[] pattern) {
if (pattern[0]!=-1 && pattern[0]!=c[x-1][y-1]) return false;
if (pattern[1]!=-1 && pattern[1]!=c[x-1][y ]) return false;
if (pattern[2]!=-1 && pattern[2]!=c[x-1][y+1]) return false;
if (pattern[3]!=-1 && pattern[3]!=c[x ][y+1]) return false;
if (pattern[4]!=-1 && pattern[4]!=c[x+1][y+1]) return false;
if (pattern[5]!=-1 && pattern[5]!=c[x+1][y ]) return false;
if (pattern[6]!=-1 && pattern[6]!=c[x+1][y-1]) return false;
if (pattern[7]!=-1 && pattern[7]!=c[x ][y-1]) return false;
return true;
}
// Match one of the 8 patterns
private boolean matchOneOfPatterns(byte[][] c,int x,int y) {
if (matchPattern(c,x,y,pattern1)) return true;
if (matchPattern(c,x,y,pattern2)) return true;
if (matchPattern(c,x,y,pattern3)) return true;
if (matchPattern(c,x,y,pattern4)) return true;
if (matchPattern(c,x,y,pattern5)) return true;
if (matchPattern(c,x,y,pattern6)) return true;
if (matchPattern(c,x,y,pattern7)) return true;
if (matchPattern(c,x,y,pattern8)) return true;
return false;
}
/**
* Skeletonize the image using succesive thinning.
*
*/
public PlanarImage thinning(PlanarImage imag) {
BufferedImage img= imag.getAsBufferedImage();
int height= img.getHeight();
int width=img.getWidth();
// 3 columns back-buffer (original values)
byte[][]tablo=new byte[width][height];
for(int y=0;y<height;y++){
for(int x=0;x<width;x++){
byte rgb = (byte) img.getRGB(x,y);
if (rgb==-1) tablo[x][y]=1;
else tablo[x][y]=0;
}
}
byte[][] image= tablo;
byte[][] buffer = new byte[3][height];
// initialize the back-buffer
for(int y=0;y<height;y++) {
buffer[0][y]=0;
buffer[1][y]=image[0][y];
buffer[2][y]=image[1][y];
}
// loop until idempotence
for(int loop=0;;loop++) {
boolean changed=false;
// for each columns
for(int x=1;x<(width-1);x++) {
// shift the back-buffer + set the last column
byte[] swp0 = buffer[0]; buffer[0]=buffer[1]; buffer[1]=buffer[2]; buffer[2]=swp0;
for(int y=0;y<height;y++) buffer[2][y]=image[x+1][y];
// for each pixel
for(int y=1;y<(height-1);y++) {
// pixel value
int v = image[x][y];
// pixel not set -> next
if (v==0) continue;
// is a boundary/extremity ?
int currentNeighbourhood = neighbourhood(buffer,1,y);
if (currentNeighbourhood<=1) continue;
if (currentNeighbourhood>=6) continue;
// is a connection ?
int transitionsCount = transitions(image,x,y);
if (transitionsCount==1 && currentNeighbourhood<=3) continue;
// no -> remove this pixel
if (transitionsCount==1) {
changed=true;
image[x][y]=0;
continue;
}
// can we delete this pixel ?
boolean matchOne = matchOneOfPatterns(image,x,y);
// yes -> remove this pixel
if (matchOne) {
changed=true;
image[x][y]=0;
continue;
}
}
}
// no change -> return result
if (!changed) {System.out.println("non"); return imag;}
else {
int[] imageDataSingleArray = new int[width*height];
int count=0;
for(int h=0;h<height;h++)
for(int w=0;w<width;w++){
if (image[w][h]== 1 ) imageDataSingleArray[count++] = 255;
else imageDataSingleArray[count++] = 0;
}
DataBufferInt dbuffer = new DataBufferInt(imageDataSingleArray,width*height);
// Create a byte data sample model.
SampleModel sampleModel =
RasterFactory.createBandedSampleModel(DataBuffer.TYPE_INT,width,height,1);
// Create a compatible ColorModel.
ColorModel colorModel = PlanarImage.createColorModel(sampleModel);
// Create a WritableRaster.
Raster raster = RasterFactory.createWritableRaster(sampleModel,dbuffer,new Point(0,0));
// Create a TiledImage using the SampleModel and ColorModel.
TiledImage tiledImage = new TiledImage(0,0,width,height,0,0,sampleModel,colorModel);
// Set the data of the tiled image to be the raster.
tiledImage.setData(raster);
PlanarImage result = tiledImage;
ParameterBlock pbConvert = new ParameterBlock();
pbConvert.addSource(result);
pbConvert.add(DataBuffer.TYPE_BYTE);
result = JAI.create("format", pbConvert);
System.out.println(result);
return result;
}
}
}
} |
