Steve on Image Processing with MATLAB

Image processing concepts, algorithms, and MATLAB

Note

Steve on Image Processing with MATLAB has been archived and will not be updated.

Lookup tables for binary image processing—makelut and applylut

This is the second in a short series on using lookup tables for binary image neighborhood operations. See the first post for the basic idea.

The Image Processing Toolbox has two related functions:

  • applylut - Process binary image using lookup table
  • makelut - Utility function to help you construct a lookup table.

Since you have to have a lookup table in order to use applylut, let's start with makelut. It's syntax is:

 lut = makelut(f, n)

f is a function handle, and n is either 2 or 3, depending on whether your lookup table is to be used with 2-by-2 or 3-by-3 neighborhoods.

For 3-by-3 neighborhoods, makelut will call your function handle f 512 times. In each call, makelut will pass as an argument to f one of the 512 possible 3-by-3 binary neighborhoods. f simply has to return the desired output value for a given neighborhood.

For example, suppose we want the output pixel to be 1 if and only if the corresponding input neighborhood looks like this:

  1 0 0
  0 1 0
  0 0 1

The you would call makelut as follows:

pattern = [1 0 0; 0 1 0; 0 0 1];
lut = makelut(@(neighborhood) isequal(neighborhood, pattern), 3);
size(lut)
ans =

   512     1

Let's try that on a small sample image.

bw = eye(5) | fliplr(eye(5))
bw =

     1     0     0     0     1
     0     1     0     1     0
     0     0     1     0     0
     0     1     0     1     0
     1     0     0     0     1

bw2 = applylut(bw, lut)
bw2 =

     0     0     0     0     0
     0     1     0     0     0
     0     0     0     0     0
     0     0     0     1     0
     0     0     0     0     0

So we see that only two input pixels, (2,2) and (4,4), have neighborhoods that exactly match the pattern.

Here's another example: Find all "endpoint" pixels. I'll define an endpoint pixel as a foreground pixel with exactly one foreground neighbor.

endpoint_fcn = @(nhood) (nhood(2,2) ~= 0) && (sum(nhood(:)) == 2);
endpoint_lut = makelut(endpoint_fcn, 3);

Here's the result on sample image from above:

bw3 = applylut(bw, endpoint_lut)
bw3 =

     1     0     0     0     1
     0     0     0     0     0
     0     0     0     0     0
     0     0     0     0     0
     1     0     0     0     1

Only the four corner pixels are endpoints.

In my next post on this topic, I'll use makelut and applylut to play Conway's Game of Life. Look for it in a week or so.




Published with MATLAB® 7.6

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