wave_tex.tar.gz_tex_wave 车牌_wave_tex.tar_车牌 小波_车牌定位 matlab

/* MEX file to rank relevant images using probabilistic distance * * Created by: Minh Do, 27 June 1999 * * To compile: * mex -O -v rankpd.c */ #include "mex.h" #include <stdlib.h> #include <math.h> /* From Numerical Recipes */ double gammaln(double xx) { double x,y,tmp,ser; static double cof[6]={76.18009172947146,-86.50532032941677, 24.01409824083091,-1.231739572450155, 0.1208650973866179e-2,-0.5395239384953e-5}; int j; y=x=xx; tmp=x+5.5; tmp -= (x+0.5)*log(tmp); ser=1.000000000190015; for (j=0;j<=5;j++) ser += cof[j]/++y; return -tmp+log(2.5066282746310005*ser/x); } /* Kullback-Leibler distance between two generalized Gaussian pdf's */ double kldist(double a1, double b1, double a2, double b2) { double res; res = log((b1 * a2) / (b2 * a1)) + gammaln(1.0/b2) - gammaln(1.0/b1) + pow(a1/a2, b2)*exp(gammaln((b2+1.0)/b1)-gammaln(1.0/b1)) - 1.0/b1; return ((res > 0.0) ? res : 0.0); } /* Kullback-Leibler distance between two feature vectors * fv1 is supposed to be from the query image * fv2 is supposed to be from the candidate image */ double probdist(double *fv1, double *fv2, int nb) { /* Assumption on features: a, b, a, b, (next level), ... for total nb pairs corresponding to nb subbands */ int i; double dist = 0.0; for (i = 0; i < nb; i++) dist += kldist(fv1[2*i], fv1[2*i+1], fv2[2*i], fv2[2*i+1]); return dist; } /* function rr = rankpd(fs, ns) % RANKPD Rank relevant images using probabilistic distance % % Input: % fs: feature sets, one column per image % ns: (optional), number of subimages per texture class % (default 16) % % Output: % rr: rank of relevant images, one column for each query % % See also: RANKED */ void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[]) { double *fs; double *rr; int nimages, ns, nb, nf; int q, i, c, r; double *dist, dr; double *pr; fs = mxGetPr(prhs[0]); nf = mxGetM(prhs[0]); nb = nf / 2; /* 2 features per band */ nimages = mxGetN(prhs[0]); if (nrhs < 2) ns = 16; else ns = (int) *(mxGetPr(prhs[1])); /* Create/allocate output */ plhs[0] = mxCreateDoubleMatrix(ns, nimages, mxREAL); rr = mxGetPr(plhs[0]); /* Array to keep distances */ dist = (double *) malloc(nimages * sizeof(double)); /* Simulate Query by Example process */ for (q = 0; q < nimages; q++) /* each query */ { for (i = 0; i < nimages; i++) /* each image */ dist[i] = probdist(fs + q * nf, fs + i * nf, nb); c = q / ns; /* class index of the query */ /* Find the rank of the relevant images */ for (r = 0; r < ns; r++) { pr = rr + q * ns + r; /* pointer to the corresponding rank */ dr = dist[c * ns + r]; /* distance of the relevant image */ *pr = 1; /* restart */ for (i = 0; i < nimages; i++) if (dist[i] < dr) (*pr)++; } } free(dist); }