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290 lines
11 KiB
Plaintext
290 lines
11 KiB
Plaintext
/*
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This is a Optical-Character-Recognition program
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Copyright (C) 2000-2009 Joerg Schulenburg
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This program is free software; you can redistribute it and/or
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modify it under the terms of the GNU General Public License
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as published by the Free Software Foundation; either version 2
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of the License, or (at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program; if not, write to the Free Software
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Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
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see README for EMAIL-address
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the following code was send by Ryan Dibble <dibbler@umich.edu>
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The algorithm is very simple but works good hopefully.
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Compare the grayscale histogram with a mass density diagram:
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I think the algorithm is a kind of
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divide a body into two parts in a way that the mass
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centers have the largest distance from each other,
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the function is weighted in a way that same masses have a advantage
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- otsu algorithm is failing on diskrete multi color images
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TODO:
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RGB: do the same with all colors (CMYG?) seperately
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test: hardest case = two colors
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bbg: test done, using a two color gray file. Output:
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# threshold: Value = 43 gmin=43 gmax=188
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my changes:
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- float -> double
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- debug option added (vvv & 1..2)
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- **image => *image, &image[i][1] => &image[i*cols+1]
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- do only count pixels near contrast regions
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this makes otsu much better for shadowed fonts or multi colored text
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on white background
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(m) Joerg Schulenburg (see README for email address)
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ToDo:
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- measure contrast
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- detect low-contrast regions
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*/
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#include <stdio.h>
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#include <string.h>
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#define Abs(x) ((x<0)?-(x):x)
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/*======================================================================*
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* global thresholding routine *
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* takes a 2D unsigned char array pointer, number of rows, and *
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* number of cols in the array. returns the value of the threshold *
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* x0,y0,x0+dx,y0+dy are the edgepoints of the interesting region *
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* vvv is the verbosity for debugging purpose *
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*======================================================================*/
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int
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otsu (unsigned char *image, int rows, int cols,
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int x0, int y0, int dx, int dy, int vvv) {
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unsigned char *np; // pointer to position in the image we are working with
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unsigned char op1, op2; // predecessor of pixel *np (start value)
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int maxc=0; // maximum contrast (start value)
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int thresholdValue=1; // value we will threshold at
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int ihist[256]; // image histogram
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int chist[256]; // contrast histogram
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int i, j, k; // various counters
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int is, i1, i2, ns, n1, n2, gmin, gmax;
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double m1, m2, sum, csum, fmax, sb;
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// zero out histogram ...
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memset(ihist, 0, sizeof(ihist));
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memset(chist, 0, sizeof(chist));
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op1=op2=0;
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gmin=255; gmax=0; k=dy/512+1;
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// v0.43 first get max contrast, dont do it together with next step
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// because it failes if we have pattern as background (on top)
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for (i = 0; i < dy ; i+=k) {
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np = &image[(y0+i)*cols+x0];
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for (j = 0; j < dx ; j++) {
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ihist[*np]++;
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if(*np > gmax) gmax=*np;
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if(*np < gmin) gmin=*np;
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if (Abs(*np-op1)>maxc) maxc=Abs(*np-op1); /* new maximum contrast */
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if (Abs(*np-op2)>maxc) maxc=Abs(*np-op2); /* new maximum contrast */
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/* we hope that maxc will be find its maximum very fast */
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op2=op1; /* shift old pixel to next older */
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op1=*np; /* store old pixel for contrast check */
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np++; /* next pixel */
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}
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}
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// generate the histogram
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// Aug06 images with large white or black homogeneous
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// areas give bad results, so we only add pixels on contrast edges
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for (i = 0; i < dy ; i+=k) {
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np = &image[(y0+i)*cols+x0];
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for (j = 0; j < dx ; j++) {
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if (Abs(*np-op1)>maxc/4
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|| Abs(*np-op2)>maxc/4)
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chist[*np]++; // count only relevant pixels
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op2=op1; /* shift old pixel to next older */
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op1=*np; /* store old pixel for contrast check */
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np++; /* next pixel */
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}
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}
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// set up everything
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sum = csum = 0.0;
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ns = 0;
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is = 0;
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for (k = 0; k <= 255; k++) {
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sum += (double) k * (double) chist[k]; /* x*f(x) cmass moment */
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ns += chist[k]; /* f(x) cmass */
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is += ihist[k]; /* f(x) imass */
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// Debug: output to out_hist.dat?
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// fprintf(stderr,"\chistogram %3d %6d (brightness weight)", k, ihist[k]);
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}
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if (!ns) {
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// if n has no value we have problems...
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fprintf (stderr, "NOT NORMAL, thresholdValue = 160\n");
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return (160);
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}
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// ToDo: only care about extremas in a 3 pixel environment
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// check if there are more than 2 mass centers (more colors)
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// return object colors and color radius instead of threshold value
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// also the reagion, where colored objects are found
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// what if more than one background color? no otsu at all?
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// whats background? box with lot of other boxes in it
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// threshold each box (examples/invers.png,colors.png)
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// get maximum white and minimum black pixel color (possible range)
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// check range between them for low..high contrast ???
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// typical scenes (which must be covered):
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// - white page with text of different colors (gray values)
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// - binear page: background (gray=1) + black text (gray=0)
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// - text mixed with big (dark) images
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// ToDo: recursive clustering for maximum multipol moments?
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// idea: normalize ihist to max=1024 before otsu?
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// do the otsu global thresholding method
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if ((vvv&1)) // Debug
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fprintf(stderr,"# threshold: value ihist chist mass_dipol_moment\n");
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fmax = -1.0;
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n1 = 0;
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for (k = 0; k < 255; k++) {
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n1 += chist[k]; // left mass (integration)
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if (!n1) continue; // we need at least one foreground pixel
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n2 = ns - n1; // right mass (num pixels - left mass)
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if (n2 == 0) break; // we need at least one background pixel
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csum += (double) k *chist[k]; // left mass moment
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m1 = csum / n1; // left mass center (black chars)
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m2 = (sum - csum) / n2; // right mass center (white background)
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// max. dipol moment?
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// orig: sb = (double) n1 *(double) n2 * (m1 - m2) * (m1 - m2);
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sb = (double) n1 *(double) n2 * (m2 - m1); // seems to be better Aug06
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/* bbg: note: can be optimized. */
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if (sb > fmax) {
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fmax = sb;
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thresholdValue = k + 1;
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// thresholdValue = (m1 + 3 * m2) / 4;
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}
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if ((vvv&1) && ihist[k]) // Debug
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fprintf(stderr,"# threshold: %3d %6d %6d %8.2f\n",
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k, ihist[k], chist[k],
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sb/(dx*dy)); /* normalized dipol moment */
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}
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// ToDo: error = left/right point where sb is 90% of maximum?
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// now we count all pixels for background detection
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i1 = 0;
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for (k = 0; k < thresholdValue; k++) {
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i1 += ihist[k]; // left mass (integration)
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}
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i2 = is - i1; // right mass (num pixels - left mass)
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// at this point we have our thresholding value
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// black_char: value<cs, white_background: value>=cs
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// can it happen? check for sureness
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if (thresholdValue > gmax) {
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fprintf(stderr,"# threshold: Value >gmax\n");
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thresholdValue = gmax;
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}
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if (thresholdValue <= gmin) {
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fprintf(stderr,"# threshold: Value<=gmin\n");
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thresholdValue = gmin+1;
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}
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// debug code to display thresholding values
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if ( vvv & 1 )
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fprintf(stderr,"# threshold: Value = %d gmin=%d gmax=%d cmax=%d"
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" b/w= %d %d\n",
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thresholdValue, gmin, gmax, maxc, i1, i2);
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// this is a primitive criteria for inversion and should be improved
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// old: i1 >= 4*i2, but 0811qemu1.png has a bit above 1/4
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if (2*i1 > 7*i2) { // more black than white, obviously black is background
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if ( vvv & 1 )
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fprintf(stderr,"# threshold: invert the image\n");
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// we do inversion here (no data lost)
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for (i = 0; i < dy ; i++) {
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np = &image[(y0+i)*cols+x0];
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for (j = 0; j < dx ; j++) {
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*np=255-*np;
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np++; /* next pixel */
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}
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}
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thresholdValue=255-thresholdValue+1;
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}
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return(thresholdValue);
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/* range: 0 < thresholdValue <= 255, example: 1 on b/w images */
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/* 0..threshold-1 is foreground */
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/* threshold..255 is background */
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/* ToDo: min=blackmasscenter/2,thresh,max=(whitemasscenter+255)/2 */
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}
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/*======================================================================*/
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/* thresholding the image (set threshold to 128+32=160=0xA0) */
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/* now we have a fixed thresholdValue good to recognize on gray image */
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/* - so lower bits can used for other things (bad design?) */
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/* ToDo: different foreground colors, gray on black/white background */
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/*======================================================================*/
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int
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thresholding (unsigned char *image, int rows, int cols,
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int x0, int y0, int dx, int dy, int thresholdValue) {
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unsigned char *np; // pointer to position in the image we are working with
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int i, j; // various counters
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int gmin=255,gmax=0;
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int nmin=255,nmax=0;
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// calculate min/max (twice?)
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for (i = y0 + 1; i < y0 + dy - 1; i++) {
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np = &image[i*cols+x0+1];
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for (j = x0 + 1; j < x0 + dx - 1; j++) {
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if(*np > gmax) gmax=*np;
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if(*np < gmin) gmin=*np;
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np++; /* next pixel */
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}
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}
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/* allowed_threshold=gmin+1..gmax v0.43 */
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if (thresholdValue<=gmin || thresholdValue>gmax){
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thresholdValue=(gmin+gmax+1)/2; /* range=0..1 -> threshold=1 */
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fprintf(stderr,"# thresholdValue out of range %d..%d, reset to %d\n",
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gmin, gmax, thresholdValue);
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}
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/* b/w: min=0,tresh=1,max=1 v0.43 */
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// actually performs the thresholding of the image...
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// later: grayvalues should also be used, only rescaling threshold=160=0xA0
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// sometimes images have no contrast (thresholdValue == gmin)
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for (i = y0; i < y0+dy; i++) {
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np = &image[i*cols+x0];
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for (j = x0; j < x0+dx; j++) {
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*np = (unsigned char) (*np >= thresholdValue || thresholdValue == gmin ?
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(255-(gmax - *np)* 80/(gmax - thresholdValue + 1)) :
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( 0+(*np - gmin)*150/(thresholdValue - gmin )) );
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if(*np > nmax) nmax=*np;
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if(*np < nmin) nmin=*np;
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np++;
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}
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}
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// fprintf(stderr,"# thresholding: nmin=%d nmax=%d\n", nmin, nmax);
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return(128+32); // return the new normalized threshold value
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/* 0..159 is foreground */
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/* 160..255 is background */
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}
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