Ground-penetrating radar (GPR) is a mature geophysical technique that is used to map utility pipelines buried within 1.5 m of the ground surface in the urban landscape. In this work, the template-matching algorithm has been originally applied to the detection and localization of pipe signatures in two perpendicular antenna polarizations. The processing of a GPR radargram is based on four main steps. The first step consists in defining a template, usually from finite-difference time-domain simulations, made of the nearby area of the hyperbola apex associated with the mean size object to be detected in the soil, whose mean permittivity has been previously experimentally estimated. In the second step, the raw radargram is pre-processed to correct variations due to antenna coupling, then the template matching algorithm is used to detect and localize individual hyperbola signatures in an environment containing unwanted reflections, noise and overlapping signatures. The distance between the shifted template and a local zone in the radargram, based on the L1 norm, allows us to obtain a map of distances. A user-defined threshold allows us to select a reduced number of zones having a high similarity measure. In the third step, minimum or maximum discrete amplitudes belonging to a selected hyperbola curve are semi-automatically extracted in each zone. In the fourth step, the discrete hyperbola data (i, j) are fitted by a parametric hyperbola model using a non-linear least squares criterion. The algorithm was implemented and evaluated on numerical radargrams, and afterwards on experimental radargrams.