The operation matches the object model, inEdgeModel, against the input image, inImage. The inSearchRegion region restricts the search area so that only in this region the centers of the objects can be presented. The inMinScore parameter determines the minimum score of the valid object occurrence. The inMinDistance parameter determines minimum distance between any two valid occurrences (if two occurrences lie closer than inMinDistance from each other, the one with greater score is considered to be valid).

In the inImage every pixel with gradient's magnitude at least inEdgeThreshold is considered an edge pixel. Only those are later used during the matching process. To establish the value of this threshold properly the diagEdgePyramid output which shows all the edges with sufficient gradient's magnitude may be used. If the inEdgePolarityMode parameter is set to Ignore, the object occurrences in the inImage image do not have necessarily to have the same contrast as the object in the model image.

The computation time of the filter depends on the size of the model, the sizes of inImage and inSearchRegion, but also on the value of inMinScore. This parameter is a score threshold. Based on its value some partial computation can be sufficient to reject some locations as valid object instances. Moreover, the pyramid of the images is used. Thus, only the highest pyramid level is searched exhaustively, and potential candidates are later validated at lower levels. The inMinPyramidLevel parameter determines the lowest pyramid level used to validate such candidates. Setting this parameter to a value greater than 0 may speed up the computation significantly, especially for higher resolution images. However, the accuracy of the found object occurrences can be reduced. Larger inMinScore generates less potential candidates on the highest level to verify on lower levels. It should be noted that some valid occurrences with score above this score threshold can be missed. On higher levels score can be slightly lower than on lower levels. Thus, some valid object occurrences which on the lowest level would be deemed to be valid object instances can be incorrectly missed on some higher level. The diagMatchPyramid output represents all potential candidates recognized on each pyramid level and can be helpful during the difficult process of the proper parameter setting.

The outObjects.Point array contains the model reference points of the matched object occurrences. The corresponding outObjects.Angle array contains the rotation angles of the objects. The corresponding outObjects.Match array provides information about both the position and the angle of each match combined into value of Rectangle2D type. Each element of the outObjects.Alignment array contains informations about the transform required for geometrical objects defined in the context of template image to be transformed into object in the context of corresponding outObjects.Match position. This array can be later used e.g. by 1D Edge Detection or Shape Fitting categories filters.

• Connect the inImage input with the image you want to find objects on. Make sure that this image is available (the program was previously run).
• Click the "..." button at the inEdgeModel input to open the GUI for creating template matching models.
  • The template region you select on the first screen should contain characteristic edges of the object, but should not be too big. In most cases you should NOT select the entire object here!
  • IMPORTANT: The template region should encompass a clean margin of 10-30 pixels around the detected edges, so that these edges are also detected correctly at higher pyramid levels (when the template image is downsampled).
  • If edges selected for the model (displayed in red) are incomplete or excessive try manipulating inSmoothingStdDev, inEdgeMagnitudeThreshold and inEdgeHysteresis as in 2D Edge Detection filters.
  • Make sure that the inMinAngle / inMaxAngle range corresponds to the expected range of object rotations. This can have big influence on execution time.
  • If you expect the object to appear at different scales, modify the inMinScale and inMaxScale parameters. Use it with care as it affects the speed.
  • Do not use simultaneously wide ranges of rotations and scaling as the resulting model may become extremely large.
  • On the second page (after clicking "Next") define the object rectangle that you want to get as the results. Please note that the rotation of this rectangle defines the object rotation, which is constrained by the inMinAngle / inMaxAngle parameters.
• You can use EnhanceMultipleObjectMatches filter to fine-tune the results. A great example of usage is presented in the CreateGoldenTemplate2 filter.
• If an object is not detected, first try decreasing inMaxPyramidLevel, then try decreasing inMinScore.
• If all the expected objects are correctly detected, try achieving higher performance by increasing inMaxPyramidLevel and inMinScore.
• Please note, that due to the pyramid strategy used for speeding-up computations, some objects whose score would finally be above inMinScore may be not found. This may be surprising, but this is by design. The reason is that the minimum value is used at different pyramid levels and many objects exhibit lower score at higher pyramid levels. They get discarded before they can be evaluated at the lowest pyramid level. Decrease inMinScore experimentally until all objects are found.
• If precision of matching is not very important, you can also gain some performance by increasing inMinPyramidLevel.
• If the performance is still not satisfactory, go back to model definition and try reducing the range of rotations and scaling as well as the precision-related parameters: inAnglePrecision, inScalePrecision and inEdgeCompleteness.
• To obtain high accuracy of matching make sure that the edges visible on the diagEdgePyramid output are not too thick. Increase inEdgeThreshold to make them thinner.
• Also consider increasing inEdgeThreshold if there is much noise on the diagEdgePyramid output.
• Verify accuracy of the matching by checking the outObjectEdges output. If the accuracy is lower than expected, make sure that inMinPyramidLevel = 0, try increasing inEdgeThreshold and also consider higher values for inAnglePrecision during model creation.
• To further improve matching accuracy use the EnhanceMultipleObjectMatches filter.
• If the object being detected can be darker or brighter than the background on different images, use the inEdgePolarityMode parameter set to Ignore.
• If the object being detected is only partially visible or its shape and the model shape are not identical, use the inEdgePolarityMode parameter set to MatchWeakly.
• If there is only low noise in the object edges, use the inEdgeNoiseLevel parameter set to Low.
• Define inSearchRegion to limit possible object locations and speed-up computations. Please note, that this is the region where the outObject.Point results belong to (and NOT the region within which the entire object has to be contained).

Locating multiple objects with the edge-based method.

Read more about Local Coordinate Systems in Machine Vision Guide: Local Coordinate Systems.

Additional information about Template Matching can be found in Machine Vision Guide: Template Matching

This operation supports automatic parallelization for multicore and multiprocessor systems.

This filter is available on Basic Complexity Level.

This filter is member of LocateObjects_Edges2 filter group.

• LocateSingleObject_Edges2 – Finds a single occurrence of a predefined template on an image by comparing object edges.

• CreateEdgeModel2 – Creates a model for edge-based template matching.

• EnhanceMultipleObjectMatches – Improves accuracy of multiple object matching by adding a subpixel-precise adjustment.