Image Processing Reference
Fig. 4.22 Left : Cropped image. Center : Histogram of input. Right : Thresholded image
Fig. 4.23 Local automatic thresholding. To p ro w : Left : Input image. Center : Mean version of
input image. Right : Mean image subtracted from input. Center row : Histograms of input and mean
image subtracted from input. Bottom row : Thresholded images
els would stand out. We can estimate a background pixel by calculating the av-
erage of the neighboring pixels. 3 Doing this for all pixels will result in an esti-
mate of the background image, see Fig. 4.23 . We now subtract the input and the
background image and the result is an image with a more even illumination where
a global threshold value can be applied, see Fig. 4.23 . 4 Depending on the situa-
tion this could either be a fixed threshold value or an automatic value as describe
3 How to calculate the average is discussed in the next chapter.
4 In the subtraction process both positive and negative values can appear. Since we are only inter-
ested in the difference we take the absolute value.