Similarity Measures for Radial Data

Template-based methods for image processing hold a list of advantages over other families of methods, e.g. simplicity and ability to mimic human behaviour. However, they also demand a careful design of the pattern representatives as well as that of the operators in charge of measuring/detecting their presence in the data. This work presents a method for fingerprint analysis, specifically for singular point detection, based on template matching. The matching process sparks the need for similarity measures able to cope with radial data. As a result, we introduce the concepts of Restricted Radial Equivalence Function (RREF) and Radial Similarity Measure (RSM), further used to evaluate the perceptual closeness of scalar and vectorial pieces of radial data, respectively. Our method, which goes by the name of Template-based Singular Point Detection method (TSPD), has qualitative advantages over other alternatives, and proves to be competitive with state-of-the art methods in quantitative terms.

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