A trace comb is used to find a number of edge points. They still represent a too large amount of unstructured information to be of any use. Many of Scorpion’s image analyses tools are based on the assumption that you can find an approximately straight line fitted to most of the points. We call it robust line fit. It is called robust since it tolerates noisy points not placed along the wanted line.

The line fit picks a random pair of points and draws a line between them. Then all other points are checked and the number of points close to the line is counted. If the number is sufficiently high, we have found the line we searched for, if not, we continue to pick new random pair of points until we find a line. If this is not happening within a specific number of tries, we terminate and signal that the line is not found.

This method is in principle simple and robust, but its parameters must be set with care. First you need some margin for the points lying on the line you search. This is called fit tolerance and is the distance a point must be within to be counted as a point on the line. The tolerance must mirror the natural measuring noise. The points will be less than 1 pixel from the line under good light- and contrast conditions. Increase the tolerance and number of trace lines if the edge is unclear. Despite the noise, you can then get a very precise measure of the line. There is a risk of not finding the line even if it’s there since line fit is a stochastic process – we pick the pair of points randomly. This happens if we don’t find a suitable pair of points before giving up. Fortunately you can have some control with this having knowledge of the minimum number of “good” points within the fit tolerance, called Goodness. Finally you set the Risk to lose a line that actually exists within all the points. This value is given in PPM (Parts Per Million). It can be set to 1 if the goodness is above 50% of the number of search lines. The goodness and risk give the basis to calculate how many random pair of points to pick before giving up. When the goodness and/or risk decreases there is a cost in an increased number of calculations. We recommend however a conservative setting of these values since the searching anyway is terminated as soon as the line is found. The time of the analysis will not be higher than what the actual number of good points indicates. Be aware that if the goodness is less than 50% of the search lines you may find another line than the one you search for. If for instance your points lie along a bent line, that is two straight lines, you have no control over which of the two lines that will be found if both are large enough to fulfill the goodness setting.

Parameter guide, line fit