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| /**
* Millie : Multifunctional Library For Image Processing
*
* (c) Copyright 2009 by Humbert Florent
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; only version 2 of the License.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
* 02111-1307, USA.
*/
package millie.operator.detection;
import java.util.LinkedList;
import millie.image.Image;
import millie.operator.commons.component.ComponentSeparableOp;
/**
* Canny Filter (edge detector)
*
* @author Xavier Philippeau
*
*/
public class CannyOperator extends ComponentSeparableOp {
//private int gaussianwindow;
//private double gaussiansigma2;
private int lowvalue ;
private int highvalue;
private int[][] gaussianKernel = null;
private int gaussianKernelFactor = 0;
static private void setPixel(Image in, int x, int y, int canal, float value) {
if(x<0 || x>=in.getWidth() ||y<0 || y>=in.getHeight())
return;
in.setPixel(x,y,canal, value);
}
static private float getPixel(Image in, int x, int y, int canal) {
if(x<0 || x>=in.getWidth() ||y<0 || y>=in.getHeight())
return 0;
return in.getPixel(x,y,canal);
}
public CannyOperator(int gaussianwindow, double gaussiansigma2, int lowvalue, int highvalue) {
this.lowvalue = lowvalue;
this.highvalue = highvalue;
if(highvalue<lowvalue)
throw new IllegalArgumentException("Low value>high value");
initGaussianKernel(gaussianwindow,gaussiansigma2);
}
@Override
public void computeComponent(Image out, Image in, int canal) {
filter( out, in, canal, this.lowvalue, this.highvalue );
}
/**
* Compute the gaussian kernel G(x,y) = Exp[ - (x^2+y^2)/(2*sigma^2) ]
*
* @param window size of the kernel
* @param sigma std-dev of the gaussian
*/
private void initGaussianKernel(int window, double sigma2) {
int aperture = window/2;
this.gaussianKernel = new int[2*aperture+1][2*aperture+1];
// factor to have only integers in the kernel
int intFactor = 1000;
this.gaussianKernelFactor = 0;
for(int dy=-aperture;dy<=aperture;dy++) {
for(int dx=-aperture;dx<=aperture;dx++) {
double e = Math.exp( - (dx*dx+dy*dy) / (2*sigma2) );
int k = (int) Math.rint(intFactor * e);
this.gaussianKernel[dx+aperture][dy+aperture]=k;
this.gaussianKernelFactor += k;
}
}
}
/**
* Histogram stretching
*
* @param c Image map
*/
public static void histogramStretch(Image bp, int canal) {
int width = bp.getWidth();
int height = bp.getHeight();
// search min/max value in the image
int min=255,max=0;
for (int y=0; y<height; y++) {
for (int x=0; x<width; x++) {
int v = (int) getPixel(bp, x, y, canal);
if (v<min) min=v;
if (v>max) max=v;
}
}
// compute translation table
int color[] = new int[256];
for(int i=0;i<256;i++) {
double t = (double)(i-min)/(double)(max-min);
if (t<0) t=0;
if (t>1) t=1;
int v = (int)(255*t);
color[i] = v;
}
// replace value in the image
for (int y=0; y<height; y++) {
for (int x=0; x<width; x++) {
int v = (int) getPixel(bp, x, y, canal);
setPixel(bp, x, y, canal, color[v]);
}
}
}
/**
* Perform convolution (Image x Kernel) at a single point
*
* @param c Image map
* @param x x coord of the computation
* @param y y coord of the computation
* @param kernel the kernel matrix
* @param factor the kernel factor
* @return convolution result
*/
private int convolve(Image bp, int x, int y, int canal, int[][] kernel, int factor) {
int width = bp.getWidth();
int height = bp.getHeight();
// assume a square kernel
int aperture = kernel[0].length/2;
int v = 0;
for(int dy=-aperture;dy<=aperture;dy++) {
for(int dx=-aperture;dx<=aperture;dx++) {
int xk = x + dx;
int yk = y + dy;
if (xk<0) xk=0;
if (xk>=width) xk=width-1;
if (yk<0) yk=0;
if (yk>=height) yk=height-1;
int vk = (int) getPixel(bp, xk,yk, canal);
v += kernel[aperture+dy][aperture+dx] * vk;
}
}
v/=factor;
return v;
}
/**
* Compute the local gradient
*
* @param c Image map
* @param x x coord of the computation (int)
* @param y y coord of the computation (int)
* @return norme and direction (-pi...pi) of the gradient
*/
private double[] gradient(Image bp, int x, int y, int canal) {
int width = bp.getWidth();
int height = bp.getHeight();
int px = x - 1; // previous x
int nx = x + 1; // next x
int py = y - 1; // previous y
int ny = y + 1; // next y
// limit to image dimension
if (px < 0) px = 0;
if (nx >= width) nx = width - 1;
if (py < 0) py = 0;
if (ny >= height) ny = height - 1;
// Intesity of the 8 neighbors
int Ipp = (int) getPixel(bp, px,py, canal);
int Icp = (int) getPixel(bp, x,py, canal);
int Inp = (int) getPixel(bp, nx,py, canal);
int Ipc = (int) getPixel(bp, px, y, canal);
int Inc = (int) getPixel(bp, nx, y, canal);
int Ipn = (int) getPixel(bp, px,ny, canal);
int Icn = (int) getPixel(bp, x,ny, canal);
int Inn = (int) getPixel(bp, nx,ny, canal);
// Local gradient
double r2 = 2.8284271247; // 2*Math.sqrt(2)
double gradx = (Inc-Ipc)/2.0 + (Inn-Ipp)/r2 + (Inp-Ipn)/r2; // horizontal + 2 diagonals
double grady = (Icn-Icp)/2.0 + (Inn-Ipp)/r2 + (Ipn-Inp)/r2; // vertical + 2 diagonals
// compute polar coordinates
double norme = Math.sqrt(gradx*gradx+grady*grady);
double angle = Math.atan2(grady, gradx);
// multiply norme by 8/3, to have the same values as Sobel Kernel 3x3
return new double[] { norme*2.6666666667, angle };
}
/**
* Compute the local gradient (subpixel with bilinear interpolation)
*
* @param c Image map
* @param x x coord of the computation (double)
* @param y y coord of the computation (double)
* @return norme and direction (-pi...pi) of the gradient
*/
private double[] gradientInterpolated(Image bp, double x, double y, int canal) {
double wx = x - (int)x;
double wy = y - (int)y;
double[] Gpp = gradient(bp,(int)x,(int)y, canal);
double[] Gnp = gradient(bp,(int)x+1,(int)y, canal);
double[] Gpn = gradient(bp,(int)x,(int)y+1, canal);
double[] Gnn = gradient(bp,(int)x+1,(int)y+1, canal);
double norme = (1-wx)*(1-wy)*Gpp[0] + wx*(1-wy)*Gnp[0] + (1-wx)*wy*Gpn[0] + wx*wy*Gnn[0];
double angle = (1-wx)*(1-wy)*Gpp[1] + wx*(1-wy)*Gnp[1] + (1-wx)*wy*Gpn[1] + wx*wy*Gnn[1];
return new double[] { norme, angle };
}
/**
* compute if a position is a local maxima
*
* @param c Image map
* @param x x coord of the computation
* @param y y coord of the computation
* @return true if position is a local maxima
*/
private boolean isLocalMaxima(Image bp, int x, int y, int canal) {
// gradient at current position
double[] grad = gradient(bp,x,y, canal);
// gradient direction
double gx = Math.cos(grad[1]);
double gy = Math.sin(grad[1]);
// gradient value at next position in the gradient direction
double nx = x + gx;
double ny = y + gy;
double[] gradn = gradientInterpolated(bp,nx,ny, canal);
// gradient value at previous position in the gradient direction
double px = x - gx;
double py = y - gy;
double[] gradp = gradientInterpolated(bp,px,py, canal);
// is the current gradient value a local maxima ?
double EPSILON=1E-7;
if ((grad[0]-gradn[0])<EPSILON) return false;
if ((grad[0]-gradp[0])<EPSILON) return false;
return true;
}
/**
* Perfom Canny filtering
*
* @param c Image map
* @param lowThreshold low value of the hysteresis
* @param highThreshold high value of the hysteresis
* @return filtered image map
*/
public void filter(Image out, Image c,int canal, int lowThreshold, int highThreshold) {
int LOWSTATE=92, HIGHSTATE=255;
int width = c.getWidth();
int height = c.getHeight();
Image bpg = new Image(c.getWidth(), c.getHeight(), c.getNumComponents());
// Gaussian filter
for (int y=0; y<height; y++) {
for (int x=0; x<width; x++) {
int v = convolve(c,x,y, canal, this.gaussianKernel,this.gaussianKernelFactor);
setPixel(bpg, x,y,canal, v);
}
}
// histogram stretching (compensate the loss of energy caused by gaussian filtering)
histogramStretch(bpg, canal);
// list of pixels above highThreshold
LinkedList<int[]> highpixels = new LinkedList<int[]>();
// gradient thresholding
for (int y=0; y<height; y++) {
for (int x=0; x<width; x++) {
// gradient intesity
double g = gradient(bpg,x,y, canal)[0];
// low-threshold -> not an edge
if (g<lowThreshold) continue;
// not a local maxima -> not an edge
if (!isLocalMaxima(bpg,x,y, canal)) continue;
// high-threshold -> is an edge
if (g>highThreshold) {
setPixel(out, x,y, canal, HIGHSTATE);
highpixels.addLast(new int[]{x,y});
continue;
}
// between thresholds -> "unknown state" (depends of neighbors)
setPixel(out, x,y, canal, LOWSTATE);
}
}
// edge continuation
int[] dx8 = new int[] {-1, 0, 1, 1, 1, 0,-1,-1};
int[] dy8 = new int[] {-1,-1,-1, 0, 1, 1, 1, 0};
while(!highpixels.isEmpty()) {
int[] pixel = highpixels.removeFirst();
int x=pixel[0], y=pixel[1];
// move low-state pixel to high-state
for(int k=0;k<8;k++) {
if (getPixel(out, x+dx8[k], y+dy8[k], canal)==LOWSTATE) {
setPixel(out,x+dx8[k], y+dy8[k], canal, HIGHSTATE);
highpixels.addLast(new int[]{x+dx8[k], y+dy8[k]});
}
}
}
// keep only high-state pixels
for (int y=0; y<height; y++)
for (int x=0; x<width; x++)
if (getPixel(out, x, y, canal)!=HIGHSTATE) setPixel(out,x,y,canal,0);
}
} |
