nonmax_suppression_dir ( ImgAmp, ImgDir : ImageResult : Mode : )

Suppress non-maximum points on an edge.

nonmax_suppression_dir suppresses all points in the regions of the image ImgAmp for which the gray values are no local (directed) maximum. ImgDir is a direction image giving the direction perpendicular for the local maximum (Unit: 2 degrees, i.e., 50 degrees are coded as 25 in the image). Such images are returned by edges__, for example. Two modes of operation can be selected:

   'nms'
           Each point in the image is tested whether its gray value
           is a local maximum perpendicular to its direction.  In
           this mode only the two neighbors closest to the given
           direction are examined.  If one of the two gray values is
           greater than the point to be tested, it is suppressed
           (i.e., removed from the input region; the corresponding
           gray value remains unchanged).

  'inms'
           Like 'nms'; however, the two gray values for the test
           are obtained by interpolation from four adjacent points.


Parameters

ImgAmp (input_object)
image(-array) -> object
Amplitude (gradient magnitude) image.

ImgDir (input_object)
image(-array) -> object
Direction image.

ImageResult (output_object)
image(-array) -> object
Image with thinned edge regions.

Mode (input_control)
string -> string
Select non-maximum-suppression or interpolating NMS.
Default value: 'nms'
List of values: 'nms', 'inms'


Result

nonmax_suppression_dir returns TRUE if all parameters are correct. The behaviour with respect to the input images and output regions can be determined by setting the values of the flags 'no_object_result', 'empty_region_result', and 'store_empty_region' with set_system. If necessary, an exception is raised.


Possible Predecessors

edges__, sobel_dir


Possible Successors

threshold__, hysteresis_threshold__


Alternatives

nonmax_suppression_amp, grey_skeleton__, max1__


See also

skeleton


References

S.Lanser: "Detektion von Stufenkanten mittels rekursiver Filter nach Deriche"; Diplomarbeit; Technische Universität München, Institut für Informatik, Lehrstuhl Prof. Radig; 1991.

J.Canny: "Finding Edges and Rows in Images"; Report, AI-TR-720; M.I.T. Artificial Intelligence Lab., Cambridge; 1983.



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