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Hough transform: Difference between revisions
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inputData(args[2].toInt(), args[3].toInt(), minContrast).writeOutputImage(args[1])
}</lang>
=={{header|Maple}}==
<lang Maple>with(ImageTools):
img := Read("pentagon.png")[..,..,1]:
img_x := Convolution (img, Matrix ([[1,2,1], [0,0,0],[-1,-2,-1]])):
img_y := Convolution (img, Matrix ([[-1,0,1],[-2,0,2],[-1,0,1]])):
img := Array (abs (img_x) + abs (img_y), datatype=float[8]):
countPixels := proc(M)
local r,c,i,j,row,col:
row := Array([]);
col := Array([]);
r,c := LinearAlgebra:-Dimensions(M);
for i from 1 to r do
for j from 1 to c do
if M[i,j] <> 0 then
ArrayTools:-Append(row, i, inplace=true):
ArrayTools:-Append(col, j, inplace=true):
end if:
end do:
end do:
return row,col:
end proc:
row,col := countPixels(img);
pTheta := proc(acc,r,c,x,y)
local j, pos:
for j from 1 to c do
pos := ceil(x*cos((j-1)*Pi/180)+y*sin((j-1)*Pi/180)+r/2):
acc[pos,j] := acc[pos,j]+1;
end do:
end proc:
HoughTransform := proc(img,row,col)
local r,c,pMax,theta,numThetas,numPs,acc,i:
r,c := LinearAlgebra:-Dimensions(img);
pMax := ceil(sqrt(r^2+c^2)):
theta := [seq(evalf(i), i = 1..181, 1)]:
numThetas := numelems(theta):
numPs := 2*pMax+1:
acc := Matrix(numPs, numThetas, fill=0,datatype=integer[4]):
for i from 1 to numelems(row) do
pTheta(acc,numPs,numThetas,col[i],row[i]):
end do:
return acc;
end proc:
result :=HoughTransform(img,row,col);
Embed(Scale(FitIntensity(Create(result)), 1..500,1..500));</lang>
=={{header|Mathematica}} / {{header|Wolfram Language}}==
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