Dynamic elastic image stretching technique applied to thermographic images

Abstract
A method of automatically ‘stretching’ a series of hand thermograms to a standard form is described. It is based on an elastic model which has the iterative and co-operative properties of relaxation labelling, while not requiring large storage space for label updating. The model was chosen to be iterative because it is difficult to produce a low-error association in a single pass. At each iteration some of the mutual differences between image pairs are removed, making the association between the new pairs more reliable. In this way the system gradually makes its way towards a match. The experiments described in this paper show that mismatches decrease with each iteration, and thus the reliability of both local and global matches is increased. The method is co-operative because a feature at one location influences decisions made in its surrounding area. Nearest neighbour relationships are used to derive local difference vectors between features. These vectors are combined in a weighted averaging scheme to produce corrected difference vectors which are then applied to an image to create a new image for further matching. An FFT based technique has been developed to enhance the efficiency of the corrected difference vector evaluation. The method has been found to be efficient and cost effective for 2-dimensional image matching.

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