How to remove the for loop in this code?

Hi, I am working on a code related to matching score calculation which is provided below:
ref_points=size(tpol,1); %number of rows=number of referenence image points
in_points=size(ipol,1); %number of rows=number of input image points
radsize=7*ones(ref_points,1);
angsize=11* ones(ref_points,1);
radlow=-radsize./2;radhigh=radsize./2;anglow=-angsize./2;anghigh=angsize./2;
epsillon=10;
mscore=0;
for i=1:ref_points
for j=1:in_points
rdiff=tpol(i,1)-ipol(j,1);
ediff=tpol(i,2)-ipol(j,2);
thetadiff=tpol(i,3)-ipol(j,3);
if ((radlow(i) < rdiff) && (rdiff < radhigh(i)) && (anglow(i) < ediff) && ...
(ediff < anghigh(i)) && (abs(thetadiff) < epsillon) && ...
(tpol(i,4)==ipol(j,4)))
mscore=mscore+1;
tpol(i,4)=3; %Change type
end
end
end
end
I am interested to reduce the for loop as it takes high computation time. It would be very helpful if anyone could guide me through this. Thanks in advance.

Answers (1)

Andrei Bobrov
Andrei Bobrov on 26 May 2016
Edited: Andrei Bobrov on 26 May 2016
r = [-3.5 3.5];
a = [-5.5 5.5];
ep = 10;
ti = bsxfun(@minus,tpol,permute(ipol,[3 2 1]));
p = all([bsxfun(@gt,ti(:,1:2,:),[r(1),a(1)]) & bsxfun(@lt,ti(:,1:2,:),[r(2),a(2)]),...
ti(:,3,:) < ep, ti(:,4,:) == 0],2);
mscore = nnz(p);
tpol(any(p,3),4) = 4;

4 Comments

I tried this code, but it gives an error when I execute the line with variable p. It says too many input arguments. Am I missing something here? Thank you.
Attach your data (tpol, ipol).
Corrected.
The first mat file has equal number of ipol and tpol data (same values)as both are same image to be matched. Whereas the second mat file has different data i.e. two different images are being matched.
I was trying to figure out the problem, it seems that
(tpol(i,4)==ipol(j,4)))
provides a different value when compared to
ti(:,4,:) == 0
The logic is correct. But the answer do not match. The rest of the "if conditions" work and provide the same answer. It would be helpful if you could help me solve this.

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Asked:

on 26 May 2016

Commented:

on 15 Jun 2016

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