Ubiquitous vortical structures are considered to act as a natural source of various solar plasma phenomena, for example, a wide range of magnetohydrodynamic waves and jet excitations. This work aims to develop an advanced vortex detection algorithm based on the Γ method and using a separable convolution kernel technique. This method is applied to detect and analyze the photospheric vortices in 3D realistic magnetoconvection numerical and observational data. We present the advanced Γ method (AGM), and our results indicate that the AGM performs with better accuracy in comparison with the original Γ method. The AGM allows us to identify small- and large-scale vortices with no vortex interposition and without requiring the changing of the threshold. In this way, the nondetection issue is mostly prevented. It was found that the Γ method failed to identify the large and longer-lived vortices, which were detected by the AGM. The size of the detected vortical structures tends to vary over time, with most vortices shrinking toward their end. The vorticity at the center is also not constant, presenting a sharp decay as the vortex ceases to exist. Due to its capability of identifying vortices with minimum nondetection, the vortex properties—such as lifetime, geometry, and dynamics—are better captured by the AGM than by the Γ method. In this era of new high-resolution observation, the AGM can be used as a precise technique for identifying and performing statistical analysis of solar atmospheric vortices.
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