Herror ::nonmax_suppression_amp (
    Hobject ImgAmp,
    Hobject *ImageResult,
    const HTuple &Mode
)
HImage HImage::NonmaxSuppressionAmp (
    const HTuple &Mode
) const
HImageArray HImageArray::NonmaxSuppressionAmp (
    const HTuple &Mode
) const

Suppress non-maximum points on an edge.

::nonmax_suppression_amp suppresses in the regions of the image ImgAmp all points whose gray values are not local (directed) maxima. In contrast to ::nonmax_suppression_dir, a direction image is not needed. Two modes of operation can be selected:

   'hvnms'
           A point is labeled as a local maximum if its gray value
           is larger than or equal to the gray values within a seach
           space of $\pm$ 5 pixels, either horizontally or vertically.
           Non-maximum points are removed from the region, gray
           values remain unchanged.

   'loc_max'
           A point is labeled as a local maximum if its gray value
           is larger than or equal to the gray values of its eight
           neighbors.


Parameters

ImgAmp (input_object)
image(-array) -> Hobject: HImage(Array) ( byte )
Amplitude (gradient magnitude) image.

ImageResult (output_object)
image(-array) -> Hobject * : HImage(Array) ( byte )
Image with thinned edge regions.

Mode (input_control)
string -> HTuple.char *
Select horizontal/vertical or undirected NMS.
Default value: 'hvnms'
List of values: 'hvnms', 'loc_max'


Result

::nonmax_suppression_amp returns H_MSG_TRUE if all parameters are correct. The behavior 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

::sobel_amp


Possible Successors

::threshold, ::hysteresis_threshold


Alternatives

::gray_skeleton, ::local_max, ::gray_dilation_rect


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, MA; 1983.


Module

Region processing



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