int
Statistic::ajustement(QVector<double> &Xi,QVector<double> &Yi,int n)
{
QVector<double> r(5),lnXi(100),lnYi(100),logXi(100),logYi(100),invXi(100);
//corrélation pour linéaire
r[0]=val_abs(corr(Xi,Yi,n));
//corrélation pour exponetielle
lntab(Yi,lnYi,n);
r[1]=val_abs(corr(Xi,lnYi,n));
//corrélation pour puissance
logtab(Xi,logXi,n);
logtab(Yi,logYi,n);
r[2]=val_abs(corr(logXi,logYi,n));
//corrélation pour inverse
invtab(Xi,invXi,n);
r[3]=val_abs(corr(invXi,Yi,n));
//corrélation pour logarithmique
lntab(Xi,lnXi,n);
r[4]=val_abs(corr(lnXi,Yi,n));
//Test du meilleur ajustement
return rmax(r);
}
int HrPwWindow::fit(QVector<double> &Xi,QVector<double> &Yi,int n)
{
QVector<double> r(5),lnXi(100),lnYi(100),logXi(100),logYi(100),invXi(100);
//Linear correlation
r[0]=val_abs(corr(Xi,Yi,n));
//Exponential correlation
lnarray(Yi,lnYi,n);
r[1]=val_abs(corr(Xi,lnYi,n));
//Power correlation
logarray(Xi,logXi,n);
logarray(Yi,logYi,n);
r[2]=val_abs(corr(logXi,logYi,n));
//Inverse correlation
invarray(Xi,invXi,n);
r[3]=val_abs(corr(invXi,Yi,n));
//Logarithmic correlation
lnarray(Xi,lnXi,n);
r[4]=val_abs(corr(lnXi,Yi,n));
//Best fit test
return rmax(r);
}
main ()
{
int i,j,k;
for (i=0; i < PICTURE_VERTICAL_SIZE; i++) {
for (j=PICTURE_HORIZONTAL_OFFSET; j < PICTURE_HORIZONTAL_SIZE+PICTURE_HORIZONTAL_OFFSET; j++) {
image_original[i][j-PICTURE_HORIZONTAL_OFFSET] = Y_test[i][j];
}
}
for (i=0; i < PICTURE_VERTICAL_SIZE; i++) {
for (j=PICTURE_HORIZONTAL_OFFSET; j < PICTURE_HORIZONTAL_SIZE+PICTURE_HORIZONTAL_OFFSET; j++) {
image_test[i][j-PICTURE_HORIZONTAL_OFFSET] = Y_test[i][j];
}
}
for (i=0; i < PICTURE_VERTICAL_SIZE; i++) {
for (j=PICTURE_HORIZONTAL_OFFSET; j < PICTURE_HORIZONTAL_SIZE+PICTURE_HORIZONTAL_OFFSET; j++) {
image_back[i][j-PICTURE_HORIZONTAL_OFFSET] = Y_back[i][j];
}
}
printf("Starting Motion Detection Application: \n\n");
printf("__attribute__((section(\".heapl2ram\"))) pixel Y_back[%d][%d] = \n{\n",PICTURE_VERTICAL_SIZE,PICTURE_HORIZONTAL_SIZE);
print_image_vect((pixel*)image_back);
printf("};\n");
printf("__attribute__((section(\".heapl2ram\"))) pixel Y_test[%d][%d] = \n{\n",PICTURE_VERTICAL_SIZE,PICTURE_HORIZONTAL_SIZE);
print_image_vect((pixel*)image_test);
printf("};\n");
printf("Subtraction and binarization treshold \n\n");
sub_image((pixel*)image_test, (pixel*)image_back);
print_image((pixel*)image_test);
max_pixel= max_image((pixel*)image_test);
printf("Max pixel = %d \n\n",max_pixel);
printf("Binarization \n\n");
binarisation((pixel*)image_test, (int)max_pixel*3/10,1,0);
print_image((pixel*)image_test);
printf("Erosion \n\n");
erosion((pixel*)image_test,KERNEL_SIZE,(pixel*)image_back);
print_image((pixel*)image_back);
printf("Dilatation \n\n");
dilatation((pixel*)image_back,KERNEL_SIZE ,(pixel*)image_test_out);
print_image((pixel*)image_test_out);
printf("Sobel Horizontal \n\n");
convolution_rect((pixel*)image_test_out, KERNEL_SIZE, sobel1,(pixel*)image_test);
val_abs((pixel*)image_test);
print_image((pixel*)image_test);
printf("Sobel Vertical \n\n");
convolution_rect( (pixel*)image_test_out, KERNEL_SIZE, sobel2,(pixel*)image_back);
val_abs((pixel*)image_back);
print_image((pixel*)image_back);
printf("Final Sum \n\n");
sum_image((pixel*)image_test, (pixel*)image_back);
binarisation((pixel*)image_test, 1,0,1);
print_image((pixel*)image_test);
printf("Final Multiplication \n\n");
multiply((pixel*)image_test, (pixel*)image_original);
printf("__attribute__((section(\".heapl2ram\"))) pixel Y_golden[%d][%d] = \n{\n",PICTURE_VERTICAL_SIZE,PICTURE_HORIZONTAL_SIZE);
print_image_vect((pixel*)image_test);
printf("};\n\n");
printf("Motion Detection Application Completed\n");
}
