  Lock-in Thermography (LIT) is a type of Infrared Thermography (IRT) that can
be used as a useful non-destructive testing (NDT) technique for the detection
of subsurface anomalies in objects. Currently, LIT fails to estimate the
thickness at a point on the tested object. This makes LIT unable to figure out
the 3-dimensional geometry of an object. In this project, two techniques of
identifying the geometry of an object using LIT are discussed. The main idea of
both techniques is to find a relationship between the parameters obtained from
LIT and the thickness at each data point. Technique I builds a numerical
function that models the relationship between thickness, Lock-In phase, and
other parameters. The function is then inverted for thickness estimation.
Technique II is a quantitative method, in which a database is created with six
dimensions - thickness, Lock-In phase, Lock-In amplitude and three other
parameters, based on data obtained from LIT experiments or simulations.
Estimated thickness is obtained by retrieving data from the database. The
database can be improved based on Principal Component Analysis. Evaluation of
the techniques is done by measuring root-mean-square deviation, and calculating
successful rate with different tolerances. Moreover, during the application of
the techniques, Stochastic Gradient Descent can be used to determine the time
when sufficient data have been collected from LIT measurement to generate the
estimated geometry accurately.
