Package com.openinventor.imageviz.engines.mathematicalmorphology.hitormissandskeleton

The Hit-or-miss and Skeleton category contains engines used to produce simplified representations of the objects in an image, while preserving their geometrical structure.

See: Description

Class Summary

Class	Description
SoApplyMorphologicalLutProcessing2d	SoApplyMorphologicalLutProcessing2d engine allows to apply a morphological look up table on a 2D image.
SoApplyMorphologicalLutProcessing2d.SbApplyMorphLutDetail	Results details of morphological Lut processing.
SoApplyMorphologicalLutProcessing3d	SoApplyMorphologicalLutProcessing3d engine allows to apply a morphological look up table on a 3D image.
SoApplyMorphologicalLutProcessing3d.SbApplyMorphLutDetail	Results details of morphological Lut processing.
SoCentroidProcessing2d	SoCentroidProcessing2d engine The SoCentroidProcessing2d engines computes the centroid of object.
SoEndPointsProcessing2d	SoEndPointsProcessing2d engine The SoEndPointsProcessing2d engine is a point detector that selects end points of a skeleton, i.e.
SoEndPointsProcessing3d	SoEndPointsProcessing3d image filter The SoEndPointsProcessing3d engine is a point detector that selects end points of a skeleton, i.e.
SoInfluenceZonesProcessing	SoInfluenceZonesProcessing engine The SoInfluenceZonesProcessing engine computes the skeleton by Influence Zone (SKIZ).
SoInteriorPointsProcessing2d	SoInteriorPointsProcessing2d engine The SoEndPointsProcessing2d engine is a point detector that computes interior points of object.
SoIsolatedPointsProcessing2d	SoIsolatedPointsProcessing2d engine The SoIsolatedPointsProcessing2d engine is a point detector that selects object made up of a single point.
SoIsolatedPointsProcessing3d	SoIsolatedPointsProcessing3d engine The SoIsolatedPointsProcessing3d engine is a point detector that selects objects made up of a single point.
SoPruneProcessing2d	SoPruneProcessing2d engine The SoPruneProcessing2d engine prunes the result of a skeletonization.
SoPruningProcessing3d	SoPruneProcessing3d engine The SoPruneProcessing3d engine prunes the result of a skeletonization.
SoSkeletonProcessing2d	SoSkeletonProcessing2d engine computes the morphological skeleton of objects.
SoTriplePointsProcessing2d	SoTriplePointsProcessing2d engine The SoTriplePointsProcessing2d engine is a point detector that selects triple points of a skeleton.

Enum Summary

Enum	Description
SoApplyMorphologicalLutProcessing2d.MatchingActions	Action to use for matching and no-matching fields.
SoApplyMorphologicalLutProcessing3d.MatchingActions	Action to use for matching and no-matching fields.
SoPruningProcessing3d.PruningModes

Package com.openinventor.imageviz.engines.mathematicalmorphology.hitormissandskeleton Description

The Hit-or-miss and Skeleton category contains engines used to produce simplified representations of the objects in an image, while preserving their geometrical structure. The representations may then be used to calculate length, direction, etc. or to detect special topological structures such as end or triple points (number of crossings).

Morphological LUT

A morphological LUT (Look Up Table) allows to move in a binary image some predefined configurations of neighborhood and apply a criteria when this configuration matches or not. Creating a morphological LUT

First a kernel has to be defined to test if a given pixel matches a criteria or not. The kernel is made of classical binary pixel values : 0, 1 and a specific one: 2 which means 'don't care'.

For example:

A LUT to convert a binary image from an 8 neighbors connexity to 4 neighbors connexity can be defined testing if a given pixel has a neighbour in the north east, north west, south west and south east directions.

These kernels have to be added one by one to build the LUT, using the addKernel method. The first kernel has to be inserted with the mode NEW, that indicates the LUT has to be reset before to add this kernel inside. Other kernels have to be ineserted with the mode OR to indicate to look for this kernels or one of the previous.

• In the 2D case 2 power 9 configurations of neighborhood are possible. The addKernel method function fills an array of 512 elements to build the LUT.
• In the 3D case 2 power 27 configurations of neighborhood are theorically possible. A 5 bits reduction is applied. The addKernel method function fills an array of 4194304 elements to build the LUT.

  Applying a morphological LUT

  Once the LUT is created, it has to be specified what has to be done with the pixels that match the LUT and those that do not. Two flag fields are available to specify the different actions: flagTrue if the pixel matches and flagFalse if it does not. There are 4 possible values :

• OUTPUT_ZERO : Force the output value to zero
• OUPUT_ONE : Force the output value to one
• OUTPUT_CHANGE : invert the output value
• OUPUT_UNCHANGE : let the output value unchanged.

For example : to change the connexity from 8 neighbors connexity to 4 , if the pixel matches the criteria the output value has to be forced to 0 and if it does not it has to be let unchanged. Therefore flagTrue = OUTPUT_ZERO and flagFalse = OUPUT_UNCHANGE.

Thinning, thickening and hit-or-miss operation with Morphological LUT

As a consequence morphological LUT's can be used to perform classical neighborhood operations such as thinning, thickening and hit-or-miss :

Skeletonization

A skeletonization is a transformation based on the thinning of connected components until a line is achieved. A skeleton is obtained by successive thinnings until convergence, using the L configuration and rotating it. The structuring element is: where means "don't care".

Point detectors

Once a skeleton is computed it may be useful to detect specific configurations of points. The point detectors uses hit-or-miss transforms (HMT) to select target points. The following engines are point detectors : SoEndPointsProcessing2d, SoInteriorPointsProcessing2d, SoIsolatedPointsProcessing2d.