# Extreme Scale Changes

PatMax can find patterns at a wide range of scale changes between the trained model and the run-time images. Increasing scale changes in the run-time image can affect PatMax performance and accuracy. You should keep in mind the following points about the effect of scale changes on PatMax:

- The presence or absence of scale change itself has no effect on PatMax speed or accuracy.
- The effect of increasing scale change is extremely image-dependent.
- If you are searching for extremely small, simple patterns, train a larger pattern, preferably using a shape description.

As the size of the scale change between the trained pattern and the run-time pattern instance becomes very large, several factors come into play. These factors are different depending on whether your application uses patterns trained from acquired images or patterns trained from shape descriptions.

Note: All of the numbers discussed in this section are approximate. The specific performance of PatMax and the effect of specific scale changes is dependent on the content of the images used for pattern training and pattern location. You should conduct your own tests using a range of images to determine the best PatMax parameter settings for your application.