/* * edtaa3() * * Sweep-and-update Euclidean distance transform of an * image. Positive pixels are treated as object pixels, * zero or negative pixels are treated as background. * An attempt is made to treat antialiased edges correctly. * The input image must have pixels in the range [0,1], * and the antialiased image should be a box-filter * sampling of the ideal, crisp edge. * If the antialias region is more than 1 pixel wide, * the result from this transform will be inaccurate. * * By Stefan Gustavson (stefan.gustavson@gmail.com). * * Originally written in 1994, based on a verbal * description of the SSED8 algorithm published in the * PhD dissertation of Ingemar Ragnemalm. This is his * algorithm, I only implemented it in C. * * Updated in 2004 to treat border pixels correctly, * and cleaned up the code to improve readability. * * Updated in 2009 to handle anti-aliased edges. * * Updated in 2011 to avoid a corner case infinite loop. * */ /* Copyright (C) 2009 Stefan Gustavson (stefan.gustavson@gmail.com) 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; either version 3 of the License, or (at your option) any later version. 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. The GNU General Public License is available on . */ #include /* * Compute the local gradient at edge pixels using convolution filters. * The gradient is computed only at edge pixels. At other places in the * image, it is never used, and it's mostly zero anyway. */ void computegradient(double *img, int w, int h, double *gx, double *gy) { int i,j,k; double glength; #define SQRT2 1.4142136 for(i = 1; i < h-1; i++) { // Avoid edges where the kernels would spill over for(j = 1; j < w-1; j++) { k = i*w + j; if((img[k]>0.0) && (img[k]<1.0)) { // Compute gradient for edge pixels only gx[k] = -img[k-w-1] - SQRT2*img[k-1] - img[k+w-1] + img[k-w+1] + SQRT2*img[k+1] + img[k+w+1]; gy[k] = -img[k-w-1] - SQRT2*img[k-w] - img[k+w-1] + img[k-w+1] + SQRT2*img[k+w] + img[k+w+1]; glength = gx[k]*gx[k] + gy[k]*gy[k]; if(glength > 0.0) { // Avoid division by zero glength = sqrt(glength); gx[k]=gx[k]/glength; gy[k]=gy[k]/glength; } } } } // TODO: Compute reasonable values for gx, gy also around the image edges. // (These are zero now, which reduces the accuracy for a 1-pixel wide region // around the image edge.) 2x2 kernels would be suitable for this. } /* * A somewhat tricky function to approximate the distance to an edge in a * certain pixel, with consideration to either the local gradient (gx,gy) * or the direction to the pixel (dx,dy) and the pixel greyscale value a. * The latter alternative, using (dx,dy), is the metric used by edtaa2(). * Using a local estimate of the edge gradient (gx,gy) yields much better * accuracy at and near edges, and reduces the error even at distant pixels * provided that the gradient direction is accurately estimated. */ double edgedf(double gx, double gy, double a) { double df, glength, temp, a1; if ((gx == 0) || (gy == 0)) { // Either A) gu or gv are zero, or B) both df = 0.5-a; // Linear approximation is A) correct or B) a fair guess } else { glength = sqrt(gx*gx + gy*gy); if(glength>0) { gx = gx/glength; gy = gy/glength; } /* Everything is symmetric wrt sign and transposition, * so move to first octant (gx>=0, gy>=0, gx>=gy) to * avoid handling all possible edge directions. */ gx = fabs(gx); gy = fabs(gy); if(gx 1.0) a = 1.0; if(a < 0.0) a = 0.0; // Clip grayscale values outside the range [0,1] if(a == 0.0) return 1000000.0; // Not an object pixel, return "very far" ("don't know yet") dx = (double)xi; dy = (double)yi; di = sqrt(dx*dx + dy*dy); // Length of integer vector, like a traditional EDT if(di==0) { // Use local gradient only at edges // Estimate based on local gradient only df = edgedf(gx, gy, a); } else { // Estimate gradient based on direction to edge (accurate for large di) df = edgedf(dx, dy, a); } return di + df; // Same metric as edtaa2, except at edges (where di=0) } // Shorthand macro: add ubiquitous parameters dist, gx, gy, img and w and call distaa3() #define DISTAA(c,xc,yc,xi,yi) (distaa3(img, gx, gy, w, c, xc, yc, xi, yi)) void edtaa3(double *img, double *gx, double *gy, int w, int h, short *distx, short *disty, double *dist) { int x, y, i, c; int offset_u, offset_ur, offset_r, offset_rd, offset_d, offset_dl, offset_l, offset_lu; double olddist, newdist; int cdistx, cdisty, newdistx, newdisty; int changed; double epsilon = 1e-3; /* Initialize index offsets for the current image width */ offset_u = -w; offset_ur = -w+1; offset_r = 1; offset_rd = w+1; offset_d = w; offset_dl = w-1; offset_l = -1; offset_lu = -w-1; /* Initialize the distance images */ for(i=0; i 0) // If non-zero distance or not set yet { c = i + offset_u; // Index of candidate for testing cdistx = distx[c]; cdisty = disty[c]; newdistx = cdistx; newdisty = cdisty+1; newdist = DISTAA(c, cdistx, cdisty, newdistx, newdisty); if(newdist < olddist-epsilon) { distx[i]=newdistx; disty[i]=newdisty; dist[i]=newdist; olddist=newdist; changed = 1; } c = i+offset_ur; cdistx = distx[c]; cdisty = disty[c]; newdistx = cdistx-1; newdisty = cdisty+1; newdist = DISTAA(c, cdistx, cdisty, newdistx, newdisty); if(newdist < olddist-epsilon) { distx[i]=newdistx; disty[i]=newdisty; dist[i]=newdist; changed = 1; } } i++; /* Middle pixels have all neighbors */ for(x=1; x 0) // If not already zero distance { c = i+offset_l; cdistx = distx[c]; cdisty = disty[c]; newdistx = cdistx+1; newdisty = cdisty; newdist = DISTAA(c, cdistx, cdisty, newdistx, newdisty); if(newdist < olddist-epsilon) { distx[i]=newdistx; disty[i]=newdisty; dist[i]=newdist; olddist=newdist; changed = 1; } c = i+offset_lu; cdistx = distx[c]; cdisty = disty[c]; newdistx = cdistx+1; newdisty = cdisty+1; newdist = DISTAA(c, cdistx, cdisty, newdistx, newdisty); if(newdist < olddist-epsilon) { distx[i]=newdistx; disty[i]=newdisty; dist[i]=newdist; olddist=newdist; changed = 1; } c = i+offset_u; cdistx = distx[c]; cdisty = disty[c]; newdistx = cdistx; newdisty = cdisty+1; newdist = DISTAA(c, cdistx, cdisty, newdistx, newdisty); if(newdist < olddist-epsilon) { distx[i]=newdistx; disty[i]=newdisty; dist[i]=newdist; changed = 1; } } /* Move index to second rightmost pixel of current row. */ /* Rightmost pixel is skipped, it has no right neighbor. */ i = y*w + w-2; /* scan left, propagate distance from right */ for(x=w-2; x>=0; x--, i--) { olddist = dist[i]; if(olddist <= 0) continue; // Already zero distance c = i+offset_r; cdistx = distx[c]; cdisty = disty[c]; newdistx = cdistx-1; newdisty = cdisty; newdist = DISTAA(c, cdistx, cdisty, newdistx, newdisty); if(newdist < olddist-epsilon) { distx[i]=newdistx; disty[i]=newdisty; dist[i]=newdist; changed = 1; } } } /* Scan rows in reverse order, except last row */ for(y=h-2; y>=0; y--) { /* move index to rightmost pixel of current row */ i = y*w + w-1; /* Scan left, propagate distances from below & right */ /* Rightmost pixel is special, has no right neighbors */ olddist = dist[i]; if(olddist > 0) // If not already zero distance { c = i+offset_d; cdistx = distx[c]; cdisty = disty[c]; newdistx = cdistx; newdisty = cdisty-1; newdist = DISTAA(c, cdistx, cdisty, newdistx, newdisty); if(newdist < olddist-epsilon) { distx[i]=newdistx; disty[i]=newdisty; dist[i]=newdist; olddist=newdist; changed = 1; } c = i+offset_dl; cdistx = distx[c]; cdisty = disty[c]; newdistx = cdistx+1; newdisty = cdisty-1; newdist = DISTAA(c, cdistx, cdisty, newdistx, newdisty); if(newdist < olddist-epsilon) { distx[i]=newdistx; disty[i]=newdisty; dist[i]=newdist; changed = 1; } } i--; /* Middle pixels have all neighbors */ for(x=w-2; x>0; x--, i--) { olddist = dist[i]; if(olddist <= 0) continue; // Already zero distance c = i+offset_r; cdistx = distx[c]; cdisty = disty[c]; newdistx = cdistx-1; newdisty = cdisty; newdist = DISTAA(c, cdistx, cdisty, newdistx, newdisty); if(newdist < olddist-epsilon) { distx[i]=newdistx; disty[i]=newdisty; dist[i]=newdist; olddist=newdist; changed = 1; } c = i+offset_rd; cdistx = distx[c]; cdisty = disty[c]; newdistx = cdistx-1; newdisty = cdisty-1; newdist = DISTAA(c, cdistx, cdisty, newdistx, newdisty); if(newdist < olddist-epsilon) { distx[i]=newdistx; disty[i]=newdisty; dist[i]=newdist; olddist=newdist; changed = 1; } c = i+offset_d; cdistx = distx[c]; cdisty = disty[c]; newdistx = cdistx; newdisty = cdisty-1; newdist = DISTAA(c, cdistx, cdisty, newdistx, newdisty); if(newdist < olddist-epsilon) { distx[i]=newdistx; disty[i]=newdisty; dist[i]=newdist; olddist=newdist; changed = 1; } c = i+offset_dl; cdistx = distx[c]; cdisty = disty[c]; newdistx = cdistx+1; newdisty = cdisty-1; newdist = DISTAA(c, cdistx, cdisty, newdistx, newdisty); if(newdist < olddist-epsilon) { distx[i]=newdistx; disty[i]=newdisty; dist[i]=newdist; changed = 1; } } /* Leftmost pixel is special, has no left neighbors */ olddist = dist[i]; if(olddist > 0) // If not already zero distance { c = i+offset_r; cdistx = distx[c]; cdisty = disty[c]; newdistx = cdistx-1; newdisty = cdisty; newdist = DISTAA(c, cdistx, cdisty, newdistx, newdisty); if(newdist < olddist-epsilon) { distx[i]=newdistx; disty[i]=newdisty; dist[i]=newdist; olddist=newdist; changed = 1; } c = i+offset_rd; cdistx = distx[c]; cdisty = disty[c]; newdistx = cdistx-1; newdisty = cdisty-1; newdist = DISTAA(c, cdistx, cdisty, newdistx, newdisty); if(newdist < olddist-epsilon) { distx[i]=newdistx; disty[i]=newdisty; dist[i]=newdist; olddist=newdist; changed = 1; } c = i+offset_d; cdistx = distx[c]; cdisty = disty[c]; newdistx = cdistx; newdisty = cdisty-1; newdist = DISTAA(c, cdistx, cdisty, newdistx, newdisty); if(newdist < olddist-epsilon) { distx[i]=newdistx; disty[i]=newdisty; dist[i]=newdist; changed = 1; } } /* Move index to second leftmost pixel of current row. */ /* Leftmost pixel is skipped, it has no left neighbor. */ i = y*w + 1; for(x=1; x