An MRF approach for interpreting thermochromic paint

Thermochromic paint, paint that changes colour according to the maximum temperature it has experienced, has a variety of uses within the automotive industry. Currently interpretation is performed manually by a human operator. This paper addresses the task of automatic interpretation, specifically addressing problems relating to feature space ambiguity. We derive a cost function to overcome these problems and utilise this within a simulated annealing framework. The method was developed using synthetic data which models the causes of ambiguity, and results are presented for real image data derived from paint-coated industrial parts