pbinarization

Performs binary thresholding on image and graph.

Synopsis

pbinarization low high [-m mask] [im_in|-] [im_out|-]

Description

pbinarization classifies pixels of the input image im_in into 2 clusters. Pixels values that are lower than low or greater than high are set to 0; other values are set to 255:

   if im_in[p] ≥ low and im_in[p] ≤ high
   then im_out[p]=255;
   else im_out[p]=0;

If high is lower than low then pbinarization performs an inverse thresholding:

   if im_in[p] < high or im_in[p] > low
   then im_out[p]=255;
   else im_out[p]=0;

For multispectral and color images, the threshold is compared with the min or max pixel value of each band. For graph, pbinarization operates on graph nodes.

Parameters

low and high specify the gray level bounds. Values are from the gray levels of the input image (eg. [0..255] for byte image, [-2147483648..+2147483648] for long integer image).

Tip: If high is lower than low then pbinarization performs an inverse thresholding.
Tip: If high is greater than the maximum gray level then high is set with the maximum value (respectively for low).

Inputs

im_in: an image or a graph.

Outputs

im_out: an image of bytes (Img2duc, Img3duc) or a graph.

Result

Returns SUCCESS or FAILURE.

Examples

Segments the tangram.pan image in 2 classes, background and tangram pieces:

   pbinarization 100 1e30 tangram.pan out.pan

C++ prototype

Errc PBinarization( const Img2duc &im_in, Img2duc &im_out, float low, float high );

Version française

Seuillage binaire d'une image.

Author: Régis Clouard