  A given six dimensional vector represents a 3D straight line in Plucker
coordinates if its coordinates satisfy the Klein quadric constraint. In many
problems aiming to find the Plucker coordinates of lines, noise in the data
and other type of errors contribute for obtaining 6D vectors that do not
correspond to lines, because of that constraint. A common procedure to overcome
this drawback is to find the Plucker coordinates of the lines that are closest
to those vectors. This is known as the Plucker correction problem. In this
article we propose a simple, closed-form, and global solution for this problem.
When compared with the state-of-the-art method, one can conclude that our
algorithm is easier and requires much less operations than previous techniques
(it does not require Singular Value Decomposition techniques).
