Adaptive Threshold
The Adaptive Threshold module is used in uneven lighting conditions when you need to segment a lighter foreground object
from its background. In many lighting situations shadows or dimming of light cause thresholding problems
as traditional thresholding considers the entire image brightness. Adaptive Thresholding will perform binary thresholding
(i.e. it creates a black and white image) by analyzing each pixel with respect to its local neighborhood. This localization
allows each pixel to be considered in a more adaptive environment.
The algorithm will consider each pixel one at a time, calculate the mean of the local neighborhood 'window size' (x-windowSize/2, y-windowSize/2, x+windowSize/2, y+windowSize/2)
and thresholds the current pixel to white if the difference between the calculated mean and the current pixel value
is lower than the 'mean offset'.
The example below shows an image from our line following tutorial. In this
image the sides of the line image are dimmed due to uneven lighting. Adaptive Thresholding can solve this problem as
long as the neighborhood considered (the pixel window) is large enough.
Interface
Instructions
1. Specify a window size large enough to reduce unwanted lighting
2. Specify the mean offset
Example
| Source | Adaptive Threshold |
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See Also
Threshold
Auto_Threshold
For more information
HIPR2 - Adaptive Thresholding
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