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===
segmentation
------------
``bbox_mcmill``
```````````````
[object] **bbox_mcmill** ([object *glyphs*], float *section_search_size* = 1.00, float *noise_mltplk* = 1.00, float *large_mltplk* = 20.00, float *stdev_mltplk* = 5.00)
:Operates on: ``Image`` [OneBit]
:Returns: [object]
:Category: OCR/segmentation
:Defined in: bbox_merging_mcmillan.py
:Author: Robert Butz, Karl MacMillan
Returns the textlines from image as connected components.
The segmentation method is adapted from McMillan's segmentation method
in roman_text.py. It allows a more individual segmentation through
parameterization.
Options:
*glyphs*:
This list can be build out of a ``cc_analysis``. On default, this
parameter is blank, which will cause the function to call
``cc_analysis`` itself.
*section_search_size*
This optional parameter adjusts the calculated avg_glyph_size by
multipling its value (default=1).
*noise_mltplk*
With this optional parameter one can adjust the noise_recognition
rate independently from the calculated avg_glyph_size (default = 1).
Values greater than 1 let the noise_removal detect bigger noise
(but maybe even glyphs). Chose smaller values to avoid assigning
small glyphs to noise.
*large_mltplk*
Analog to noise_mltplk one can set this parameter to manipulate the
recognition of very large ccs according to the avg_glyph_size
(default=20). Higher values lead to a better acceptance of
above-average ccs. Beneficial, for example for big capital
initials at the beginning of paragraphs such as seen in bibles.
*stdev_mltplk*
This parameter affects the line finding algorithm by excluding
abnormally tall glyphs (default=5). The standard deviation will
be calculated and multiplied by this parameter.
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