i have to apply RANSAC algorithm on an image toget the best fit in license plate detection. how can it be possible?

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ACHAMMA JACOB
ACHAMMA JACOB 2019-1-16
评论： ezhil K 2019-1-21
function [bestModel,bestInliers,bestOutliers,bestError] = ransac(thresError,N,d,iterations)
syms inliers outliers ni no;
% model
bestModel = [];
bestInliers = [];
bestOutliers = [];
bestError = inf;
reply = input('Random generation (1) or input data (2)?\n');
if (reply == 1)
data= rand(2,N);
else
data = input('Enter the data matrix in 2xN format.\n');
end
for i=1:iterations
randomP = randperm(N);
p1 = [ data(1,randomP(1)), data(2,randomP(1)) ];
p2 = [ data(1,randomP(2)), data(2,randomP(2)) ];
inliers = [];
outliers = [];
ni = 0;
no = 0;
a_model = ( p1(2) - p2(2) )/ ( p1(1) - p2(1) );
b_model = p1(2) - a_model*p1(1);
totalError = 0;
for p=1:N
point = data(:,p);
error = abs( data(1,p)*a_model + b_model - data(2,p) )/ sqrt( a_model^2 + 1);
if( thresError < error )
outliers(:,no+1) = point;
no = no+1;
else
totalError = totalError + error;
inliers(:,ni+1) = point;
ni = ni+1;
end
end % data iteration end
% check model
if ( bestError > totalError && d < ni )
bestModel = [a_model,b_model];
bestInliers = inliers;
bestOutliers = outliers;
bestError = totalError;
end
end % main iteration end
return;

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