LocateMultiplePointPatterns

The filter finds locations of a pattern of points in the set of input points. The possible rotations and scales of the found occurrences can be fully controlled using proper values of inAllowRotation, inMinAngle, inMaxAngle, inAllowScale, inMinScale and inMaxScale parameters.

The location routine consists of three phases. Only the inTilingFactor and inMinInitialScore parameters have an effect on the initial phase. Internally, the whole plane is then divided into square tiles which size depends on inTilingFactor and the average distance between two points from inPoints. A transformation becomes a candidate to be a valid pattern occurrence if at least inMinInitialScore fraction of pattern points reside in the right tiles. The candidate transformation proceeds to the second phase, where it is refined to be possibly best fitted to the data points. The result transformation is considered to be a valid output alignment if at least inMinScore fraction of aligned pattern points are at most inMaxDeviation away from their closest data points.

The end phase's purpose is to select the output alignments according to the inMinDistance and inDisjointObjectsOnly parameters values. The ultimate output is chosen so no two aligned pattern centers are closer than inMinDistance from themselves and, if inDisjointObjectsOnly parameter is set, no two aligned patterns cover the same data point.

The most difficult part to achieve reliable results seems to be the proper setting of the inTilingFactor parameter. Because of its existence, the algorithm will work especially well when the pattern consists of not too many points and distances between them are more or less equal i.e. the ratio of the greatest distance between pattern points and the smallest distance between pattern points is small. If this is not the case and the default value for inTilingFactor does not work well, one should try to adjust the value keeping in mind that the greater values should be used when the pattern visible in the inPoints is distorted and the smaller values will work best when only small distortion is present. In case of further problems with choosing the right inTilingFactor value, one can also try lowering inMinInitialScore value.

The filter performance depends heavily on the number of the pattern points. Because of that fact, it is highly advisable for the pattern to be as small as possible. The performance can be poor even for patterns with more than 15 points. Note that the shape of the pattern also matters. The execution time for symmetrical patterns is generally bigger than for asymmetrical ones.

This filter can throw an exception to report error. Read how to deal with errors in Error Handling.

List of possible exceptions:

This filter is available on Advanced Complexity Level.

This filter is member of LocatePointPatterns filter group.

• LocateSinglePointPattern – Finds an occurrence of the pattern in the input points.