fdprep.c

eye detection sample in matlab. Eyetrackers can analyze a driver’s level of attentiveness while driv

#include "mex.h"

#define LOW_BOUND 30
#define HIGH_BOUND 220
#define IN_BOUND_PERCENTAGE 170
/* mexFunction is the gateway routine for the MEX-file. */ 
void
mexFunction( int nlhs, mxArray *plhs[],
             int nrhs, const mxArray *prhs[] )
{
  int        i,m,n;
  unsigned char *in,*out,*searchpos;
  unsigned short *x,*y;
  // [sample,y,x] = fdprep(image,searchpos)
  if (nlhs!=3)
      mexErrMsgTxt("Must have exactly 3 outputs [sample,y,x] = fdprep (...)\n");
  if (nrhs!=2)
      mexErrMsgTxt("Must have exactly two input2: image and searchpos .\n");
  if ((!mxIsUint8(prhs[0]))||(!mxIsUint8(prhs[1])))
      mexErrMsgTxt("Both inputs must be of type UINT8.\n");
  
  in= (unsigned char*)mxGetData(prhs[0]);
  searchpos = (unsigned char*)mxGetData(prhs[1]);
  m=mxGetM(prhs[0]);
  n=mxGetN(prhs[0]);
  if ((mxGetM(prhs[1])!=m)||(mxGetN(prhs[1])!=n))
    mexErrMsgTxt("Both input matrices must be of the same size");
  if ((m<20)||(n<20))
    return;
  
  out = mxCalloc(360*(m-20+1)*(n-20+1),sizeof(char));
  y = mxCalloc((m-20+1)*(n-20+1),sizeof(short));
  x = mxCalloc((m-20+1)*(n-20+1),sizeof(short));
  {
    int size;
    unsigned char* pchar;
    unsigned short* pshort;
    size=DoCalc(in,searchpos,out,x,y,n,m);
    plhs[0] = mxCreateNumericMatrix(360,size,mxUINT8_CLASS,mxREAL);
    pchar = (unsigned char*)mxGetData(plhs[0]);
    for (i=0; i<size*360; i++)
        pchar[i]=out[i];
    mxFree(out);
    
    plhs[1] = mxCreateNumericMatrix(1,size,mxUINT16_CLASS,mxREAL);
    pshort = (unsigned short*)mxGetData(plhs[1]);
    for (i=0; i<size; i++)
        pshort[i]=y[i];
    mxFree(y);

    plhs[2] = mxCreateNumericMatrix(1,size,mxUINT16_CLASS,mxREAL);
    pshort = (unsigned short*)mxGetData(plhs[2]);
    for (i=0; i<size; i++)
        pshort[i]=x[i];
    mxFree(x); 
  }
}


int DoCalc(unsigned char *in,
           unsigned char *searchpos,
           unsigned char *out,
           unsigned short *x_array, 
           unsigned short* y_array, 
           int w, 
           int h)
{
	unsigned int index360[360];
	int i,j,curr,x,y;
	double sum,sqsum,var;
	int hist[256];
	char str[100];
	unsigned char* pout=out;
	int sample_index=0;
	// initializations
	curr=0;
	for (i=0; i<20; i++)
	{
		int startj, endj;
		if (i<4)
		{
			startj=4-i;
			endj = 19-(4-i);
		}
		else 
		if (i>15)
		{
			startj=4-(19-i);
			endj = 19-(4-(19-i));
		}
		else
		{
			startj=0;
			endj=19;
		}
		for (j=startj; j<=endj; j++)
		{
			index360[curr++]=j+i*h;
		}
	}
	
	// build histogram
	for (y=0; y<=h-20;y++)
	{
		for (x=0; x<=w-20; x++)
		{
			int offset = y+x*h;
            if (searchpos[offset]==0)
                continue;
			for(i=0; i<256; i++)
				hist[i]=0;
			sum=0;
			sqsum=0;
			for (i=0; i<360;i++)
			{
				pout[i]=in[offset+index360[i]];
				hist[pout[i]]++;
				sum+= pout[i];
				sqsum += pout[i]*pout[i];
			}
			// If variance is too low, ignore current sample
			var = (sqsum - sum*sum/360)/360;
			if (var <300)
			    continue;
			//else
			//    mexPrintf("var = %f\t y=%d, x=%d\n",var,y,x);
			// build probability density function
			for (i=1; i<256;i++)
				hist[i]= hist[i]+hist[i-1];
			for (i=0; i<256;i++)
				hist[i]= hist[i]*255/360;
			// If histogram is too bright or too dark, ignore it
			if ((hist[HIGH_BOUND]-hist[LOW_BOUND])<IN_BOUND_PERCENTAGE)
			    continue;
			
			// apply histogram equalization
			for (i=0; i<360; i++)
				pout[i]=hist[pout[i]];
			x_array[sample_index]=x+1;
			y_array[sample_index]=y+1;
			sample_index++;
			pout+=360;
		}
	}
	
	return sample_index;
}