## 1 Introduction
A frequently used alloy within the context of MAM is Maraging steel, a ferrous alloy whose name is derived from the junction of the terms martensite and ageing as it obtains its mechanical strength from the precipitation hardening phenomenon resulting from ageing heat treatments [23]. Maraging alloys have very low levels of C as it contributes to the formation of fragile carbides, such as TiC [24]. Furthermore, it contains appreciable quantities of Ti, Al and Co and large quantities (between 18 and 25 weight %) of Ni, with the latter leading to a soft but heavily dislocated martensite [25] upon quenching. These alloys find application in the automotive, aerospace, military and tool die industries [26]. One of the advantages of this alloy, apart from its exceptional combination of high strength and toughness, is its printability: a recent research work [27] conducted 16 single tracks in which the energy density (expressed in Equation (1)) oscillated from 66.7 J mm\({}^{-2}\) and 416.7 J mm\({}^{-2}\), returning beads with dilution proportions between 55% and 75%, values generally considered too excessive [12]; Additionally, researchers [28] developed processing maps for 18 Ni300, concluding that laser powers larger than 1200 W with a laser spot size of 2.55 mm resulted in porosities below 0.7%, although speeds below 9 mm s\({}^{-1}\) for the same power setting lead to dilution proportions (given by Equation (2)) below 12.5%. Recent work [29], in which 18 Ni300 tensile specimens were obtained from nine different parameter combinations, concluded that energy density values over 180 J mm\({}^{-2}\) lead to components with near 100% density, with the laser power being considered the most influential parameter on tensile property. Investigations into the influence of the powder feeding rate in depositing precipitation hardened steel on 304L stainless steel substrates were also conducted [30], where the dilution proportion was larger for increased feeding rates. DED-related processes have different levels of in-situ control: recent research monitored the melting pool geometry during wire arc additive manufacturing to control for the bead's geometry and symmetry [31]; additional research was conducted on the use of a structured light system in the development of a real-time monitoring tool to aid the repair of an engine component [32]. Moreover, research towards establishing process maps that guide the deposition process towards avoiding lack-of-fusion and keyhole porosities has been conducted [33]. However, the aforementioned research mainly focuses on in-situ measurements and control over process variables, rather than output analysis, which is the case of this research work: the workflow associated with the parameter optimisation for different materials is similar, where different combinations of inputs are used in depositing single track line beads, which are subsequently cross-sectionally cut and analysed through optical microscopy (OM). In addition to probing for defects inherent to this technology, such as entrapped gas, lack-of-fusion pores and cracking [2], several macroscopic parameters were obtained, such as the track width \(w\), height \(h\), penetration \(p\), wettability angles \(\theta_{l}\) and \(\theta_{r}\) and dilution proportion \(D_{p}\); the latter is computed as:  
\[D_{p}=\frac{A_{b}}{A_{a}+A_{b}}\cdot 100\quad[\%], \tag{2}\]  
where \(A_{a}\) and \(A_{b}\) are the areas above and below the substrate line, respectively. A schematic representation of these outputs is shown in Figure 1.  
The computation of the aforementioned bead properties is usually done manually through image processing software, such as ImageJ; the novelty of this work thus arises in the development of an algorithm, using the scikit-image [34] package for Python, to obtain properties in a reliable and automated way. The OM images used as samples for developing and testing the developed algorithm were self-obtained, pertaining to the deposition optimisation of 18 Ni300 Managing steel on H13 tool steel substrates.