Spatio-temporal relaxation labelling applied to segmented infrared image sequences

This paper present a relaxation labelling technique for enforcing local consistency of region classification, both spatially within an image and temporally between images in a sequence of images. The technique is region based as opposed to more traditional relaxation labelling techniques which are pixel based and uses region neighbours spatially within an image and temporally from previous images in the sequence. The technique is demonstrated on a sequence of 300 segmented infrared images in which the initial region labelling has been performed using texture features and neural network classifiers. The relaxation labelling is extremely successful at enforcing local consistency and is able to label regions which were too small for an initial classification