A framework for radial data comparison and its application to fingerprint analysis

Graphical abstractDisplay Omitted HighlightsWe define restricted radial equivalence functions and radial similarity functions for comparing radial data.Using these functions, we propose a fingerprint Template-based Singular Point Detection algorithm.In this algorithm, we exploit the high visibility of singular points in the Orientation Map.We experimentally compare the results of our algorithm with those obtained from other algorithms in the literature. This work tackles the comparison of radial data, and proposes comparison measures that are further applied to fingerprint analysis. First, we study the similarity of scalar and non-scalar radial data, elaborated on previous works in fuzzy set theory. This study leads to the concepts of restricted radial equivalence function and Radial Similarity Measure, which model the perceived similarity between scalar and vectorial pieces of radial data, respectively. Second, the utility of these functions is tested in the context of fingerprint analysis, and more specifically, in the singular point detection. With this aim, a novel Template-based Singular Point Detection method is proposed, which takes advantage of these functions. Finally, their suitability is tested in different fingerprint databases. Different Similarity Measures are considered to show the flexibility offered by these measures and the behavior of the new method is compared with well-known singular point detection methods.