char_threshold ( Image, HistoRegion : Characters : Percent : Threshold )

Perform a threshold segmentation for extracting characters.

char_threshold segments a single-channel image using an automatically determined threshold. It is assumed that the background of the image is bright and the foreground (the characters) are dark. First a histogram of the gray values in the image Image is computed in the points given by the region HistoRegion. Then the maximum in the histogram is computed (bright paper). Finally, the first gray value to the ``left'' of the maximum is located, which is at least Percent smaller than the maximum.


Parameters

Image (input_object)
image(-array) -> object : byte
Image to be segmented.

HistoRegion (input_object)
region -> object
Region in which the histogram is computed.

Characters (output_object)
region(-array) -> object
Dark regions (characters).

Percent (input_control)
number -> real / integer
Percentage for the gray value difference.
Default value: 95
Suggested values: 90, 92, 95, 96, 97, 98, 99, 99.5, 100
Range of values: 0.0 <= Percent <= 100.0 (lin)
Minimum increment: 0.1
Recommended increment: 0.5

Threshold (output_control)
integer(-array) -> integer
Calculated threshold.


Example
#include  "HCPP.H"
#include  

int main (int argc, char *argv[])
{
  if (argc != 2)
  {
    cout << "Usage : " << argv[0] << " 'image' " << endl;
    return (-1);
  }

  HImage       image (argv[1]),
               med;
  HWindow      w;

  w.SetDraw ("margin");
  w.SetShape ("rectangle1");
  w.SetColored (12);

  image.Display (w);

  HRegionArray reg = image.CharThreshold(5);
  HRegionArray con = reg.Connection ();

  cout << "Display image after BinThreshold segmentation " << endl;
  con.Display (w);
  w.Click ();

  return (0);
}

Possible Predecessors

anisotrope_diff__, median, illuminate__


Possible Successors

connection, select_shape, select_grey__


Alternatives

bin_threshold, auto_threshold2, auto_threshold1, histo__, histo_gauss, threshold__



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