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The mechanical characteristics of the railway superstructure are related to the properties of the \udballast, and especially to the particle size distribution of its grains. Under the constant stress-strain \udof carriages, the ballast can deteriorate over time, and consequently it should properly be monitored \udfor safety reasons. The equipment which currently monitors the railway superstructure (like the \udItalian diagnostic train Archimede) do not make any “quantitative” evaluation of the ballast. The \udaim of this paper is therefore to propose a new methodology for extracting railway ballast particle \udsize distribution by means of the image processing technique. The procedure has been tested on \uda regularly operating Italian railway line and the results have been compared with those obtained \udfrom laboratory experiments, thus assessing how effective is the methodology which could \udpotentially be implemented also in diagnostic trains in the near future

A New High-Efficiency Procedure for Aggregate Gradation Determination of the Railway Ballast by Means Image Recognition Method