function localBoxes = maxBoxVals(finalBoxes)
rects = [];
for es = 1 : length(finalBoxes)
y = finalBoxes(es, 1);
x = finalBoxes(es, 2);
y2 = finalBoxes(es, 3);
x2 = finalBoxes(es, 4);
rects = [rects ; [x, y, y2-y, x2 - x]];
end
overlaps = rectint(rects, rects);
%overlaps(logical(eye(size(overlaps)))) = 0;
[r,c] = find(overlaps > 0);
localBoxes = [];
for i = 1 : length(overlaps)
col = overlaps(:,i);
col2 = find(col > 0);
if(~length(col2) > 0)
continue;
end
localRects = [rects(i,:)];
for j = 1 : length(col2)
localRects = [localRects ; rects(col2(j),:)];
end
if(max(localRects) > 0)
minX = min(localRects(:,1));
minY = min(localRects(:,2));
maxX = max(localRects(:,1))+max(localRects(:,3));
maxY = max(localRects(:,2))+max(localRects(:,4));
localBoxes = [localBoxes ; [minX,minY,abs(maxX - minX), abs(maxY - minY)]];
end
end
localBoxes = unique(localBoxes,'rows')
end
This is what I have come up with to solve. Not vectorised and definitely not optimal, and may be some bugs, but seems to get the job done for what I need, and applies to the whole image.