The automated measurement of rock fragmentation particle size distribution in the muck during muck excavation has been developing over the last 16 years. The introduction of stereo camera imaging of the muck has provided improved automated particle segmentation for image-based measurement algorithms. Recently, a new vision system processing algorithm has been developed. The inclusion of 2D texture in the analysis has provided a significant improvement in the definition of the finer size fractions, which has resulted in the automated analysis no longer requiring calibration.The previous stereo vision system algorithm required analysis calibration to account for poor small particle' definition in the 3D surface profile. This was because of the depth perception limitations of the stereo camera system at greater than 8 m. The new algorithm has been implemented on a number of shovel-installed vision systems, and the algorithm's performance in automated analysis has been assessed against a diligent manual analysis of the same fragmentation images. The new algorithm provides improved distribution resolution and accuracy.CITATION:Noy, M J, 2015. Evaluation of a new vision system algorithm for automated fragmentation measurement from a shovel, in Proceedings 11th International Symposium on Rock Fragmentation by Blasting, pp 721-726 (The Australasian Institute of Mining and Metallurgy: Melbourne).