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标题:小妹有個C語言的源程序怎麽都編譯不出來,求各位幫忙
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kennanzhou
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小妹有個C語言的源程序怎麽都編譯不出來,求各位幫忙

哪位大哥可以幫個忙看看程序阿! *************************************** Canny.c内容如下

#include <math.h> #include <stdio.h> #define MAX #include "lib.h"

/* Scale floating point magnitudes and angles to 8 bits */ #define ORI_SCALE 40.0 #define MAG_SCALE 20.0

/* Biggest possible filter mask */ #define MAX_MASK_SIZE 20

/* Fraction of pixels that should be above the HIGH threshold */ float ratio = 0.1; int WIDTH = 0;

int trace (int i, int j, int low, IMAGE im,IMAGE mag, IMAGE ori); float gauss(float x, float sigma); float dGauss (float x, float sigma); float meanGauss (float x, float sigma); void hysteresis (int high, int low, IMAGE im, IMAGE mag, IMAGE oriim); void canny (float s, IMAGE im, IMAGE mag, IMAGE ori); void seperable_convolution (IMAGE im, float *gau, int width, float **smx, float **smy); void dxy_seperable_convolution (float** im, int nr, int nc, float *gau, int width, float **sm, int which); void nonmax_suppress (float **dx, float **dy, int nr, int nc, IMAGE mag, IMAGE ori); void estimate_thresh (IMAGE mag, int *low, int *hi);

void main (int argc, char *argv[]) { int i,j,k,n; float s=1.0; int low= 0,high=-1; FILE *params; IMAGE im, magim, oriim;

/* Command line: input file name */ if (argc < 2) { printf ("USAGE: canny <filename>\n"); printf ("Canny edge detector - reads a PGM format file and\n"); printf (" detects edges, creating 'canny.pgm'.\n"); exit (1); } printf ("CANNY: Apply the Canny edge detector to an image.\n");

/* Read parameters from the file canny.par */ params = fopen ("canny.par", "r"); if (params) { fscanf (params, "%d", &low); /* Lower threshold */ fscanf (params, "%d", &high); /* High threshold */ fscanf (params, "%f", &s); /* Gaussian standard deviation */ printf ("Parameters from canny.par: HIGH: %d LOW %d Sigma %f\n", high, low, s); fclose (params); } else printf ("Parameter file 'canny.par' does not exist.\n");

/* Read the input file */ im = Input_PBM (argv[1]); if (im == 0) { printf ("No input image ('%s')\n", argv[1]); exit (2); }

/* Create local image space */ magim = newimage (im->info->nr, im->info->nc); if (magim == NULL) { printf ("Out of storage: Magnitude\n"); exit (1); }

oriim = newimage (im->info->nr, im->info->nc); if (oriim == NULL) { printf ("Out of storage: Orientation\n"); exit (1); }

/* Apply the filter */ canny (s, im, magim, oriim); /* Hysteresis thresholding of edge pixels */ hysteresis (high, low, im, magim, oriim);

for (i=0; i<WIDTH; i++) for (j=0; j<im->info->nc; j++) im->data[i][j] = 255;

for (i=im->info->nr-1; i>im->info->nr-1-WIDTH; i--) for (j=0; j<im->info->nc; j++) im->data[i][j] = 255;

for (i=0; i<im->info->nr; i++) for (j=0; j<WIDTH; j++) im->data[i][j] = 255;

for (i=0; i<im->info->nr; i++) for (j=im->info->nc-WIDTH-1; j<im->info->nc; j++) im->data[i][j] = 255;

Output_PBM (im, "canny.pgm");

printf ("Output file is:\n"); printf (" canny.pgm - edge-only image\n"); }

float norm (float x, float y) { return (float) sqrt ( (double)(x*x + y*y) ); }

void canny (float s, IMAGE im, IMAGE mag, IMAGE ori) { int width; float **smx,**smy; float **dx,**dy; int i,j,k,n; float gau[MAX_MASK_SIZE], dgau[MAX_MASK_SIZE], z;

/* Create a Gaussian and a derivative of Gaussian filter mask */ for(i=0; i<MAX_MASK_SIZE; i++) { gau[i] = meanGauss ((float)i, s); if (gau[i] < 0.005) { width = i; break; } dgau[i] = dGauss ((float)i, s); }

n = width+width + 1; WIDTH = width/2; printf ("Smoothing with a Gaussian (width = %d) ...\n", n);

smx = f2d (im->info->nr, im->info->nc); smy = f2d (im->info->nr, im->info->nc);

/* Convolution of source image with a Gaussian in X and Y directions */ seperable_convolution (im, gau, width, smx, smy);

/* Now convolve smoothed data with a derivative */ printf ("Convolution with the derivative of a Gaussian...\n"); dx = f2d (im->info->nr, im->info->nc); dxy_seperable_convolution (smx, im->info->nr, im->info->nc, dgau, width, dx, 1); free(smx[0]); free(smx);

dy = f2d (im->info->nr, im->info->nc); dxy_seperable_convolution (smy, im->info->nr, im->info->nc, dgau, width, dy, 0); free(smy[0]); free(smy);

/* Create an image of the norm of dx,dy */ for (i=0; i<im->info->nr; i++) for (j=0; j<im->info->nc; j++) { z = norm (dx[i][j], dy[i][j]); mag->data[i][j] = (unsigned char)(z*MAG_SCALE); }

/* Non-maximum suppression - edge pixels should be a local max */

nonmax_suppress (dx, dy, (int)im->info->nr, (int)im->info->nc, mag, ori);

free(dx[0]); free(dx); free(dy[0]); free(dy); }

/* Gaussian */ float gauss(float x, float sigma) { float xx;

if (sigma == 0) return 0.0; xx = (float)exp((double) ((-x*x)/(2*sigma*sigma))); return xx; }

float meanGauss (float x, float sigma) { float z;

z = (gauss(x,sigma)+gauss(x+0.5,sigma)+gauss(x-0.5,sigma))/3.0; z = z/(PI*2.0*sigma*sigma); return z; }

/* First derivative of Gaussian */ float dGauss (float x, float sigma) { return -x/(sigma*sigma) * gauss(x, sigma); }

/* HYSTERESIS thersholding of edge pixels. Starting at pixels with a value greater than the HIGH threshold, trace a connected sequence of pixels that have a value greater than the LOW threhsold. */

void hysteresis (int high, int low, IMAGE im, IMAGE mag, IMAGE oriim) { int i,j,k;

printf ("Beginning hysteresis thresholding...\n"); for (i=0; i<im->info->nr; i++) for (j=0; j<im->info->nc; j++) im->data[i][j] = 0;

if (high<low) { estimate_thresh (mag, &high, &low); printf ("Hysteresis thresholds (from image): HI %d LOW %D\n", high, low); } /* For each edge with a magnitude above the high threshold, begin tracing edge pixels that are above the low threshold. */

for (i=0; i<im->info->nr; i++) for (j=0; j<im->info->nc; j++) if (mag->data[i][j] >= high) trace (i, j, low, im, mag, oriim);

/* Make the edge black (to be the same as the other methods) */ for (i=0; i<im->info->nr; i++) for (j=0; j<im->info->nc; j++) if (im->data[i][j] == 0) im->data[i][j] = 255; else im->data[i][j] = 0; }

/* TRACE - recursively trace edge pixels that have a threshold > the low edge threshold, continuing from the pixel at (i,j). */

int trace (int i, int j, int low, IMAGE im,IMAGE mag, IMAGE ori) { int n,m; char flag = 0;

if (im->data[i][j] == 0) { im->data[i][j] = 255; flag=0; for (n= -1; n<=1; n++) { for(m= -1; m<=1; m++) { if (i==0 && m==0) continue; if (range(mag, i+n, j+m) && mag->data[i+n][j+m] >= low) if (trace(i+n, j+m, low, im, mag, ori)) { flag=1; break; } } if (flag) break; } return(1); } return(0); }

void seperable_convolution (IMAGE im, float *gau, int width, float **smx, float **smy) { int i,j,k, I1, I2, nr, nc; float x, y;

nr = im->info->nr; nc = im->info->nc;

for (i=0; i<nr; i++) for (j=0; j<nc; j++) { x = gau[0] * im->data[i][j]; y = gau[0] * im->data[i][j]; for (k=1; k<width; k++) { I1 = (i+k)%nr; I2 = (i-k+nr)%nr; y += gau[k]*im->data[I1][j] + gau[k]*im->data[I2][j]; I1 = (j+k)%nc; I2 = (j-k+nc)%nc; x += gau[k]*im->data[i][I1] + gau[k]*im->data[i][I2]; } smx[i][j] = x; smy[i][j] = y; } }

void dxy_seperable_convolution (float** im, int nr, int nc, float *gau, int width, float **sm, int which) { int i,j,k, I1, I2; float x;

for (i=0; i<nr; i++) for (j=0; j<nc; j++) { x = 0.0; for (k=1; k<width; k++) { if (which == 0) { I1 = (i+k)%nr; I2 = (i-k+nr)%nr; x += -gau[k]*im[I1][j] + gau[k]*im[I2][j]; } else { I1 = (j+k)%nc; I2 = (j-k+nc)%nc; x += -gau[k]*im[i][I1] + gau[k]*im[i][I2]; } } sm[i][j] = x; } }

void nonmax_suppress (float **dx, float **dy, int nr, int nc, IMAGE mag, IMAGE ori) { int i,j,k,n,m; int top, bottom, left, right; float xx, yy, g2, g1, g3, g4, g, xc, yc;

for (i=1; i<mag->info->nr-1; i++) { for (j=1; j<mag->info->nc-1; j++) { mag->data[i][j] = 0;

/* Treat the x and y derivatives as components of a vector */ xc = dx[i][j]; yc = dy[i][j]; if (fabs(xc)<0.01 && fabs(yc)<0.01) continue;

g = norm (xc, yc);

/* Follow the gradient direction, as indicated by the direction of the vector (xc, yc); retain pixels that are a local maximum. */

if (fabs(yc) > fabs(xc)) {

/* The Y component is biggest, so gradient direction is basically UP/DOWN */ xx = fabs(xc)/fabs(yc); yy = 1.0;

g2 = norm (dx[i-1][j], dy[i-1][j]); g4 = norm (dx[i+1][j], dy[i+1][j]); if (xc*yc > 0.0) { g3 = norm (dx[i+1][j+1], dy[i+1][j+1]); g1 = norm (dx[i-1][j-1], dy[i-1][j-1]); } else { g3 = norm (dx[i+1][j-1], dy[i+1][j-1]); g1 = norm (dx[i-1][j+1], dy[i-1][j+1]); }

} else {

/* The X component is biggest, so gradient direction is basically LEFT/RIGHT */ xx = fabs(yc)/fabs(xc); yy = 1.0;

g2 = norm (dx[i][j+1], dy[i][j+1]); g4 = norm (dx[i][j-1], dy[i][j-1]); if (xc*yc > 0.0) { g3 = norm (dx[i-1][j-1], dy[i-1][j-1]); g1 = norm (dx[i+1][j+1], dy[i+1][j+1]); } else { g1 = norm (dx[i-1][j+1], dy[i-1][j+1]); g3 = norm (dx[i+1][j-1], dy[i+1][j-1]); } }

/* Compute the interpolated value of the gradient magnitude */ if ( (g > (xx*g1 + (yy-xx)*g2)) && (g > (xx*g3 + (yy-xx)*g4)) ) { if (g*MAG_SCALE <= 255) mag->data[i][j] = (unsigned char)(g*MAG_SCALE); else mag->data[i][j] = 255; ori->data[i][j] = atan2 (yc, xc) * ORI_SCALE; } else { mag->data[i][j] = 0; ori->data[i][j] = 0; }

} } }

void estimate_thresh (IMAGE mag, int *hi, int *low) { int i,j,k, hist[256], count;

/* Build a histogram of the magnitude image. */ for (k=0; k<256; k++) hist[k] = 0;

for (i=WIDTH; i<mag->info->nr-WIDTH; i++) for (j=WIDTH; j<mag->info->nc-WIDTH; j++) hist[mag->data[i][j]]++;

/* The high threshold should be > 80 or 90% of the pixels j = (int)(ratio*mag->info->nr*mag->info->nc); */ j = mag->info->nr; if (j<mag->info->nc) j = mag->info->nc; j = (int)(0.9*j); k = 255;

count = hist[255]; while (count < j) { k--; if (k<0) break; count += hist[k]; } *hi = k;

i=0; while (hist[i]==0) i++;

*low = (*hi+i)/2.0; }

************************************ ************************************ lib.h内容如下

/*----------------------------------------------------------------------

Grey level include file

J. R. Parker Laboratory for Computer Vision University of Calgary Calgary, Alberta, Canada

---------------------------------------------------------------------- */

#include <stdio.h> #include <math.h> #include <malloc.h>

/* The image header data structure */ struct header { int nr, nc; /* Rows and columns in the image */ int oi, oj; /* Origin */ };

/* The IMAGE data structure */ struct image { struct header *info; /* Pointer to header */ unsigned char **data; /* Pixel values */ };

#define SQRT2 1.414213562 #define BLACK 0 #define WHITE 1

typedef struct image * IMAGE;

#if defined (MAX) int PBM_SE_ORIGIN_COL=0, PBM_SE_ORIGIN_ROW=0; char **arg; int maxargs; #else extern int PBM_SE_ORIGIN_COL, PBM_SE_ORIGIN_ROW; #endif

int range (IMAGE im, int i, int j); void print_se (IMAGE p); IMAGE Input_PBM (char *fn); IMAGE Output_PBM (IMAGE image, char *filename); void get_num_pbm (FILE *f, char *b, int *bi, int *res); void pbm_getln (FILE *f, char *b); void pbm_param (char *s); struct image *newimage (int nr, int nc); void freeimage (struct image *z); void sys_abort (int val, char *mess); void copy (IMAGE *a, IMAGE b); void CopyVarImage (IMAGE *a, IMAGE *b); void Display (IMAGE x); float ** f2d (int nr, int nc);

sbmM2csA.rar (4.28 KB) 小妹有個C語言的源程序怎麽都編譯不出來,求各位幫忙

搜索更多相关主题的帖子: 小妹 
2005-06-07 13:34
kennanzhou
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这是一个用canny算子提取图像边缘的程序
我也是从网上找来的 但是急着要用
 各位大哥哥们 能帮忙 多指导一些么
2005-06-07 18:18
快速回复:小妹有個C語言的源程序怎麽都編譯不出來,求各位幫忙
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