Traditional tread depth measurements require manual utilization of a mechanical device to acquire measurements at each location of interest on a tire. Drive-over machine-vision sensors are becoming available as a means for measuring tread depth. These sensors typically consist of a laser and a camera contained in an environmentally-sealed sensor housing. Tires approach the sensor over the supporting surface, while a laser projects an illuminating line across the tread surface for capture in a digital image. This scan is evaluated to provide a single 2D contour of tread depth at the illuminated line. Advanced machine-vision sensors acquire a sequence of images, which results in a multitude of data points over a 3D region of the tread surface. Post-processing of the acquired images illustrates the observed tread pattern and establishes multiple tread depth measurements.Measurements determined by the advanced sensors from hundreds of tires were compared to manual measurements acquired with analog and digital mechanical gauges. The advanced drive-over machine-vision sensors out-perform manual measurements. Manual measurements introduced errors due to variations in the selected measurement locations on the tire tread, operation of the mechanical gauge, and limited data points. In contrast, the advanced machine vision systems consistently acquired a multitude of data points over an observed 3D region of tread surface, enabling evaluation of the tread pattern. Averaging and other post-processing analysis techniques produced accurate tread depth measurements which were not subject to operator-introduced variables.