📄 definemodel.m
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function [model] = defineModel(dx,dy,model,quantVal)
%Build a 2D Gradient histogram
%Scale image between 0 and 255
sgradX = scale(dx,[0 255]);
sgradY = scale(dy,[0 255]);
%Quantize image
qgradX = reduceGrad(sgradX,quantVal);
qgradY = reduceGrad(sgradY,quantVal);
model.qgradX = uint8(qgradX/quantVal + 1);
model.qgradY = uint8(qgradY/quantVal + 1);
sizeRegX = size(qgradX);
sizeRegY = size(qgradY);
maxheight = min([sizeRegX(1) sizeRegX(2)]);
maxwidth = min([sizeRegX(2) sizeRegY(2)]);
height = model.h(2)*2;
width = model.h(1)*2;
startX = model.center(1)-model.h(1);
startY = model.center(2)-model.h(2);
if(startX<1)
startX = 1;
end
if(startY<1)
startY=1;
end
index = uint8(256/quantVal + 1);
model.gradTable(index,index) = double(0);
model.modelDist(index,index) = double(0);
CM1=0;
%count gradient values
for y = startY:startY+height-1
for x = startX:startX+width-1
indexX = x;
indexY = y;
if(x>=maxwidth)
indexX = maxwidth;
end
if(y>=maxheight)
indexY = maxheight;
end
if(x < 1)
indexX=1;
end
if(y < 1)
indexY=1;
end
diffX = model.qgradX(indexY,indexX);
diffY = model.qgradY(indexY,indexX);
normDist = (model.center-[x y])./model.h;
kresult = epanech(normDist,1);
CM1 = CM1+kresult;
model.modelDist(diffX,diffY) = model.modelDist(diffX,diffY) + kresult;
model.gradTable(diffX,diffY) = model.gradTable(diffX,diffY) + 1;
end
end
model.C = 1/CM1;
model.modelDist = model.modelDist*model.C;
sum(sum(model.modelDist));
function [reduced] = reduceGrad(grad,quantVal);
reduced = double(grad);
reduced = quant(reduced,quantVal);
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