Georeferenced Edge Detection Analysis

I am trying to analysis the results of edge detection algorithms compared to reference data. However I am encountering a few problems. Firstly as the two matrices were of differing size I used padarray to increase the size of the smaller array to the larger one. However the problem with this was that the reference data did not always lie in the true position of the correct edges so affected my results. I am using the True Positive, False Negative, False Positive and True Negative to calculate the Total Positive Rate, Branching Factor and Quality Percentage, stated in McKeown et al. (2000), using the following code;

 function [TPR,BF,QP]= Quantify(Candidate,Reference)
    TP=sum(((Reference==1) + (Candidate==1))==2);
    FN=sum(((Reference==1) + (Candidate==0))==2);
    FP=sum(((Reference==0) + (Candidate==1))==2);
    TN=sum(((Reference==0) + (Candidate==0))==2);
    TPR = 100*TP/(TP+FN)
    BF = FP/TP
    QP = 100*TP/(TP+FP+FN)
end

The data I am using has world files associated to the data. I am therefore wondering if there is a way that I can use the world file data to compare the data against each other whilst in its correct geographic location? The datasets being compared are both logical datasets in OSGB36. Also how can I overcome the previous problems with different matrix sizes if they are first coordinate is located at different positions.

I hope this makes sense and look forward to your responses. If any more information is required please comment and I'll try to explain it further.

Andrew