Floor Finder
The Floor Finder module is used to identify the floor area within an image. The assumptions that make
this possible are that the robot or camera is on a planar floor that extends from the bottom of the
camera image outwards away from the camera. This assumption is required since the Floor Finder
module will sample the pixels in the bottom of the image area (the sample space) and use those pixels to identify similar
pixels in the rest of the image. Thus it is assumed that the floor space right in front of the robot
is relatively free from obstacles and represents a portion of the floor.
Interface
Instructions
1. Sample Shape - select the sample shape that you would like to use. The default is the
square shape that will sample more pixels than the triangle shape but may be affected
by darker pixels or non-floor pixels at the image borders. To reduce image border issues
(depending on the style of camera you are using) you can switch to the triangle sample
area that includes more pixels in the middle of the image.
You can change the width and height of the shape to include more or less pixels. The more
representative pixels that are used in the sample space the better. Increasing the sample
space will also include more pixels that are not floor space so a compromise needs
to be reached between floor and object pixels.
2. Threshold - select the threshold level that specifies how many pixels of a certain color
need to exist in the sample are before they are considered 'representative' of the floor
area. If your immediate floor space includes obstacles setting the threshold higher will
help remove those obstacle pixels from consideration. This, however, can also remove
floor pixels that are slightly discolored from the rest.
For a more adaptive way of setting the threshold chose a value from the dropdown (besides
manual) to select only the top X percent of pixels seen in the sample area as a guide for the
rest of the image. Setting this value will find which pixel occurs the most
frequently (its count) in the sample area and then set the threshold to be X percentage of that count.
This allows the threshold to change based on how consistent the sample area is and change based on
the image properties within the sample space.
3. Highlights - Often floor space (especially reflective floors) will tend to have white
highlights in them due to overhead lights. These highlights have very specific properties
that can be used to partially include them back into the floor space. As highlights
are normally bright intense spots they are normally not included within the sample space
beyond very low threshold values. Selecting the "Fill Highlights" checkbox will
analyze the current image for highlights and fill them in with white pixels. This helps
to complete a full floor space and eliminate the appearance of obstacles in the middle
of the floor.
4. Histogram Spread - As the sample space is smaller than the rest of the image it often
does not include pixels that are very close to pixels within the sample space. Increasing
the histogram spread will widen the influence pixels in the sample space have on
neighboring pixels. In this way a pixel in the sample space can also pixels
near in color to it into the representative histogram which will cause more pixels in the
rest of the image to be recognized as belonging to the sample space.
5. Result - select how the results should be presented. "Colored" refers to the original
pixel values (excluding the highlights which are always in white). "White" or "Black"
mask will set pixels to white or black depending on if they are represented in the
sample space or not.
Examples
Note that last image is the floor of a tiled reflective floor. The two large highlights are filled
in using the "Fill Highlight" option.
See Also
Wall Finder
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