In many applications, the current versus voltage curve of a photovoltaic cell, module, string, or field is acquired. A high number of samples are usually acquired, but the curve contains the main information in the open- and short-circuit points, as well as where it has a strong change in the slope. In this paper, these parts are called “the fingerprint” of the photovoltaic generator. The fingerprint allows us to recognize the working conditions of the photovoltaic generator, e.g., if it is affected by a partial shadowing or not. Saving the fingerprint and discarding the other points of the original curve allows us to minimize the memory needs for storing the curve without losing the main information content. In this paper, a numerical technique for selecting, from among the samples of the acquired current versus voltage curve of any photovoltaic generator, the ones to be included in the fingerprint is proposed. The processing steps and the memory needed to achieve the result are minimized in order to allow an implementation of the algorithm also in a low-cost processor for on-field real-time applications. The technique is validated through curves generated by using analytical models as well as by means of some curves acquired experimentally in outdoor conditions.