# Pattern Granularity

For most applications, PatMax does a good job selecting the coarse and fine pattern granularity limits. If you want to override PatMax's granularity limits, you should do so by evaluating the trained features.

Keep in mind that PatMax's strategy in choosing granularity limits is to choose the largest coarse granularity that detects features that can be reliably used to quickly locate the pattern and to choose the smallest fine granularity setting which will reliably and precisely locate the pattern.

The following are examples of when you might decide to override PatMax's settings:

- If the coarse granularity trained feature display is including features that appear not to represent actual feature boundaries, you can try increasing the coarse pattern granularity to exclude the redundant small features. This might increase the alignment speed.
- If the fine granularity trained feature display is including features that are not actually part of the pattern, such as surface texture, you could try increasing the fine pattern granularity to exclude the extraneous small features. This might improve reliability.
- If the fine granularity trained feature display does not include fine features that are part of the pattern, such as fine teeth on a gearwheel, you could try decreasing the fine pattern granularity to include the small pattern features. This might increase accuracy.

You should not attempt to override PatMax's granularity settings without carefully examining the trained feature display. In general, you should choose the granularity that produce trained features that match the features of interest in the image.

Note: When using the PatFlex algorithm, the default granularities are generally smaller due to the need for more detail. If you set your own granularities they will also be generally smaller than those you would set for other algorithms.