Analyzing and interpreting of thermograms has been increasingly employed in the diagnosis and monitoring of diseases thanks to its non-invasive, non-harmful nature and low cost. This thesis explores methods for thermal image analysis systems based on image registration for two
medical applications; skin disease diagnosis and cooling study. In the first application, a novel system is proposed to improve the diagnosis and monitoring of morphoea based on a face sketch and the published lines of Blaschko. In the latter, a novel semi-automated system is proposed to investigate a cooling mask for maxillofacial surgery patients based on thermogram data of normal subjects. In both applications, image registration based on global and local registration
methods are found inevitable. A modified normalized gradient cross-correlation (NGC) method
to reduce large geometrical differences between two multimodal images of different subjects that
are represented by smooth gray edge maps is proposed for the global registration approach. To
correct for small displacements between the global outcomes, a simple stochastic based non-rigid affine registration (NRAR) method is proposed. The NRAR method is driven by a cost function that takes into consideration the similarity between two images by a correlation coefficient. A geometric based intensity distortion to ensure only small distortions are accepted, and an overlapping pixel rate are also incorporated. Smooth deformation controlled by an exponential
Euclidean based smoothing operator is employed to only edge pixels navigated by a distance function as both the images are represented by edge maps and thus reduces computation time. The NRAR method has shown good performance in correcting for small, varying displacements
between images with fairly reliable flexibility and elasticity for both convex and concave objects
with the help of the NGC to minimize the initial displacements. A semi-automated approach that includes the NGC and/or the NRAR method followed by determination of cooling area based on the Otsu’s thresholding and a seed-based region growing method is found to achieve reliable and reproducible cooling patterns with good correlation with the clinical assessment, for potential cooling study of maxillofacial surgery patients.