# Score

For each instance of the trained pattern that PatMax finds in the run-time image, it computes a score value between 0.0 and 1.0. The score an instance receives indicates how closely it matches the trained pattern. A score of 1.0 indicates a perfect match; a score of 0.0 indicates that the pattern does not match at all.

When you specify the PatMax algorithm, PatMax scores instances on both the closeness of pattern fit (the degree to which the shape of the features in the run-time image conforms to the shape of the features in the trained pattern) and the presence of clutter (extraneous features). When you specify the PatQuick algorithm, PatMax scores instances on pattern fit only.

In considering the fit, PatMax considers the shape of the pattern. Differences in brightness or contrast (as long as the polarity is the same) are ignored. (You can specify that PatMax ignore polarity changes in addition to brightness and contrast changes.)

PatMax is somewhat tolerant of elastic stretching of the pattern. PatMax tends to return lower scores for patterns with missing or extraneous features. The following figure shows examples of patterns with elastic stretching and patterns with missing or extraneous features (called broken patterns).

In all cases, missing features lower the score an object receives. Extraneous features lower an object's score if you specify the PatMax algorithm and if you specify that PatMax consider clutter when computing scores. For more information on scoring and clutter, see the topic Ignoring Clutter When Scoring