Multi-feature hierarchical template matching using distance transforms

Abstract

We describe a multi-feature hierarchical algorithm to efficiently match N objects (templates) with am image using distance transforms (DTs). The matching is under translation, but it can cover more general transformations by generating the various transformed templates explicitly. The novel part of the algorithm is that, in addition to a coarse-to-fine search over the translation parameters, the N templates are grouped off-line into a template hierarchy based on their similarity. This way, multiple templates can be matched simultaneously at the coarse levels of the search, resulting in various speed-up factors. Furthermore, in matching, features are distinguished by type and separate DTs are computed for each type (e.g. based on edge orientations). These concepts are illustrated in the application of traffic sign detection.