# Clutter Score

The clutter score is a measure of the extent to which the found object contains features that are not present in the trained pattern.

The clutter score is the proportion of extraneous features present in the found object relative to the number of features in the trained pattern. A clutter score of 0.0 indicates that the found instance contains no extraneous features. A clutter score of 1.0 indicates that for every feature in the trained pattern there is an additional extraneous feature in the found pattern instance. The clutter score can exceed 1.0.

When PatMax computes the clutter score, it considers all features within the area in the run-time image that corresponds to the image area used to train the pattern, as shown in the following figure.

In the case of shape training, the area in which clutter affects score is defined by the training region.

Note: A common reason for using shape training is the presence of many variable and extraneous features in the images used by your application. When you locate shape-trained patterns in these images, there will likely be a large amount of clutter. In many cases, you should disable scoring clutter