In this study, we compare the performance of six fully automatic methods of within-subjects pedobarographic image registration: principal axes, modal matching, min(XOR), min(MSE), contours-based and frequency-based. These algorithms were tested on 30 control image pairs considered in previous studies. The accuracy was assessed by visual inspection and using the image similarity measures: exclusive-or (XOR) and ...
Image registration has been used to support pixel-level data analysis on pedobarographic image data sets. Some registration methods have focused on robustness and sacrificed speed, but a recent approach based on external contours offered both high computational processing speed and high accuracy. However, since contours can be influenced by local perturbations, we sought more global methods. Thus, we propose tw...
This paper presents an assignment algorithm with circular order preserving constraint. Given a cost affinity matrix and the desired percentage of correspondences, the algorithm implemented using dynamic programming determines the correspondence of type one-to-one of minimum global cost. Here, it was applied to optimize the global matching between two sets of ordered points that represent the contours of objects...
Image registration, the process of optimally aligning homologous structures in multiple images, has recently been demonstrated to support automated pixel-level analysis of pedobarographic images and, subsequently, to extract unique and biomechanically relevant information from plantar pressure data. Recent registration methods have focused on robustness, with slow but globally powerful algorithms. In this paper...
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