fv.rar_球 检测_缺陷_钢球_钢缺陷

#include <stdio.h> #include <string.h> #include <math.h> #define MAX #include "lib.h" #define OUTLINE 25 /* Function prototypes */ void main( int argc, char **argv); void shen(IMAGE im, IMAGE res); void compute_ISEF (float **x, float **y, int nrows, int ncols); float ** f2d (int nr, int nc); void apply_ISEF_vertical (float **x, float **y, float **A, float **B, int nrows, int ncols); void apply_ISEF_horizontal (float **x, float **y, float **A, float **B, int nrows, int ncols); IMAGE compute_bli (float **buff1, float **buff2, int nrows, int ncols); void locate_zero_crossings (float **orig, float **smoothed, IMAGE bli, int nrows, int ncols); void threshold_edges (float **in, IMAGE out, int nrows, int ncols); int mark_connected (int i, int j,int level); int is_candidate_edge (IMAGE buff, float **orig, int row, int col); float compute_adaptive_gradient (IMAGE BLI_buffer, float **orig_buffer, int row, int col); void estimate_thresh (double *low, double *hi, int nr, int nc); void debed (IMAGE im, int width); void embed (IMAGE im, int width); /* globals for shen operator*/ double b = 0.9; /* smoothing factor 0 < b < 1 */ double low_thresh=20, high_thresh=22; /* threshold for hysteresis */ double ratio = 0.99; int window_size = 7; int do_hysteresis = 1; float **lap; /* keep track of laplacian of image */ int nr, nc; /* nrows, ncols */ IMAGE edges; /* keep track of edge points (thresholded) */ int thinFactor; void main(int argc, char **argv) { int i,j,n,m; IMAGE im, res; FILE *params; /* Command line args - file name, maybe sigma */ if (argc < 2) { printf ("USAGE: shen <inmagefile>\n"); exit (1); } im = Input_PBM (argv[1]); if (im == 0) { printf ("Can't read input image from '%s'.\n", argv[1]); exit (2); } /* Look for parameter file */ params = fopen ("shen.par", "r"); if (params) { fscanf (params, "%lf", &ratio); fscanf (params, "%lf", &b); if (b<0) b = 0; else if (b>1.0) b = 1.0; fscanf (params, "%d", &window_size); fscanf (params, "%d", &thinFactor); fscanf (params, "%d", &do_hysteresis); printf ("Parameters:\n"); printf (" %% of pixels to be above HIGH threshold: %7.3f\n", ratio); printf (" Size of window for adaptive gradient : %3d\n", window_size); printf (" Thinning factor : %d\n", thinFactor); printf ("Smoothing factor : %7.4f\n", b); if (do_hysteresis) printf ("Hysteresis thresholding turned on.\n"); else printf ("Hysteresis thresholding turned off.\n"); fclose (params); } else printf ("Parameter file 'shen.par' does not exist.\n"); embed (im, OUTLINE); res = newimage (im->info->nr, im->info->nc); shen (im, res); debed (res, OUTLINE); Output_PBM (res, "shen.pgm"); printf ("Output file is 'shen.pgm'\n"); } void shen (IMAGE im, IMAGE res) { register int i,j; float **buffer; float **smoothed_buffer; IMAGE bli_buffer; /* Convert the input image to floating point */ buffer = f2d (im->info->nr, im->info->nc); for (i=0; i<im->info->nr; i++) for (j=0; j<im->info->nc; j++) buffer[i][j] = (float)(im->data[i][j]); /* Smooth input image using recursively implemented ISEF filter */ smoothed_buffer = f2d( im->info->nr, im->info->nc); compute_ISEF (buffer, smoothed_buffer, im->info->nr, im->info->nc); /* Compute bli image band-limited laplacian image from smoothed image */ bli_buffer = compute_bli(smoothed_buffer, buffer,im->info->nr,im->info->nc); /* Perform edge detection using bli and gradient thresholding */ locate_zero_crossings (buffer, smoothed_buffer, bli_buffer, im->info->nr, im->info->nc); free(smoothed_buffer[0]); free(smoothed_buffer); freeimage (bli_buffer); threshold_edges (buffer, res, im->info->nr, im->info->nc); for (i=0; i<im->info->nr; i++) for (j=0; j<im->info->nc; j++) if (res->data[i][j] > 0) res->data[i][j] = 0; else res->data[i][j] = 255; free(buffer[0]); free(buffer); } /* Recursive filter realization of the ISEF (Shen and Castan CVIGP March 1992) */ void compute_ISEF (float **x, float **y, int nrows, int ncols) { float **A, **B; A = f2d(nrows, ncols); /* store causal component */ B = f2d(nrows, ncols); /* store anti-causal component */ /* first apply the filter in the vertical direcion (to the rows) */ apply_ISEF_vertical (x, y, A, B, nrows, ncols); /* now apply the filter in the horizontal direction (to the columns) and */ /* apply this filter to the results of the previous one */ apply_ISEF_horizontal (y, y, A, B, nrows, ncols); /* free up the memory */ free (B[0]); free(B); free (A[0]); free(A); } void apply_ISEF_vertical (float **x, float **y, float **A, float **B, int nrows, int ncols) { register int row, col; float b1, b2; b1 = (1.0 - b)/(1.0 + b); b2 = b*b1; /* compute boundary conditions */ for (col=0; col<ncols; col++) { /* boundary exists for 1st and last column */ A[0][col] = b1 * x[0][col]; B[nrows-1][col] = b2 * x[nrows-1][col]; } /* compute causal component */ for (row=1; row<nrows; row++) for (col=0; col<ncols; col++) A[row][col] = b1 * x[row][col] + b * A[row-1][col]; /* compute anti-causal component */ for (row=nrows-2; row>=0; row--) for (col=0; col<ncols; col++) B[row][col] = b2 * x[row][col] + b * B[row+1][col]; /* boundary case for computing output of first filter */ for (col=0; col<ncols-1; col++) y[nrows-1][col] = A[nrows-1][col]; /* now compute the output of the first filter and store in y */ /* this is the sum of the causal and anti-causal components */ for (row=0; row<nrows-2; row++) for (col=0; col<ncols-1; col++) y[row][col] = A[row][col] + B[row+1][col]; } void apply_ISEF_horizontal (float **x, float **y, float **A, float **B, int nrows, int ncols) { register int row, col; float b1, b2; b1 = (1.0 - b)/(1.0 + b); b2 = b*b1; /* compute boundary conditions */ for (row=0; row<nrows; row++) { A[row][0] = b1 * x[row][0]; B[row][ncols-1] = b2 * x[row][ncols-1]; } /* compute causal component */ for (col=1; col<ncols; col++) for (row=0; row<nrows; row++) A[row][col] = b1 * x[row][col] + b * A[row][col-1]; /* compute anti-causal component */ for (col=ncols-2; col>=0; col--) for (row=0; row<nrows;row++) B[row][col] = b2 * x[row][col] + b * B[row][col+1]; /* boundary case for computing output of first filter */ for (row=0; row<nrows; row++) y[row][ncols-1] = A[row][ncols-1]; /* now compute the output of the second filter and store in y */ /* this is the sum of the causal and anti-causal components */ for (row=0; row<nrows; row++) for (col=0; col<ncols-1; col++) y[row][col] = A[row][col] + B[row][col+1]; } /* compute the band-limited laplacian of the input image */ IMAGE compute_bli (float **buff1, float **buff2, int nrows, int ncols) { register int row, col; IMAGE bli_buffer; bli_buffer = newimage(nrows, ncols); for (row=0; row<nrows; row++) for (col=0; col<ncols; col++) bli_buffer->data[row][col] = 0; /* The bli is computed by taking the difference between the smoothed image */ /* and the original image. In Shen and Castan's paper this is shown to */ /* approximate the band-limited laplacian of the image. The bli is then */ /* made by setting all values in the bli to 1 where the laplacian is */ /* positive and 0 otherwise. */ for (row=0; row<nrows; row++) for (col=0; col<ncols; col++) { if (row<OUTLINE || row >= nrows-OUTLINE || col<OUTLINE || col >= ncols-OUTLINE) continue; bli_buffer->data[row][col] = ((buff1[row][col] - buff2[row][col]) > 0.0); } return bli_buffer; } void locate_zero_crossings (float **orig, float **smoothed, IMAGE bli, int nrows, int ncols) { register int row, col; for (row=0; row<nrows; row++) { for (col=0; col<ncols; col++) { /* ignore pixels around the boundary