Is there a known algorithm for this?

From: Gerald Rosenberg (No_at_address.net)
Date: 09/19/04 

Date: 19 Sep 2004 16:47:50 EDT

In sum, I need to determine the least common denominator for the spacing
of a one dimensional array of integers give the integers have an unknown
noise component.

Alternately, I have a one-dimensional series of integers that I know
will, within an unknown error tolerance, map to a uniform interval one-
dimensional grid. I also know that the error component of the integers
is well less than the grid spacing. I need to determine the largest
best fit interval of the grid consistent with the integer data.

In practical terms, I have the Y-axis pixel baseline locations of lines
of text on a page (the Y values will have a small error component) and
need to determine for any two adjacent text lines whether they are
single spaced, 1.5 spaced, or multiple spaced.

Seems like there should be an analytic solution, but auto-correlation
doesn't seem right. Some kind of quantized best-fit?

Rather than continuing to guess, does anyone know the name of the
algorithm/class of algorithms for solving this type of problem
(something sufficient for Googling).

Is there a Java package/implementation that can solve this kind of
problem? I have looked at Colt, but it does not provide a direct
solution.

At a minimum, any thoughts on how best to solve the problem would be
appreciated.

Thanks,
Gerald

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