## 4 Discussion
### Marker-Free Measurement  
In addition to high processing rate and short latency, our system also provides marker-free DIC measurement on polished metals at a rather large field-of-view of more than 10 mm. This avoids a second disadvantage common for most current DIC systems: the need for specimen preparation. Besides the additional work, markers or speckle-paint can break or delaminate during the experiment. In addition, the markers have to withstand experimental conditions like high temperatures, and they must create unique patterns on a scale suitable for correlation. Characteristic surface (marker) generation is possible but requires certain experience and might not be allowed for industrial processes.  
According to our experience with polished specimen from aluminum, nickel-based superalloys and steel, the incidental microstructure exhibits patterns on multiple scales which are well suited for correlation. Generally, we found the noise on polished metal specimen to be lower measuring marker-free rather than using speckle-paint, presumably because the incidental microstructure of the sample surfaces exhibited a wider range of spacial frequencies allowing to exploit the full resolution of the optics. Critical are periodic structures on the specimen surface originating from polishing processes because they create non-statistical noise in the correlation result. Their impact on the sub-pixel displacement measurement was eliminated by filtering the images with a Gaussian low-pass filter.  
The reproducibility of the marker-free strain measurement was a standard deviation of \(10^{-5}\) (1\(\sigma\)) and a maximum error of \(\pm 3\times 10^{-5}\) measured by a zero-strain-test [32]. It is similar to that of IC-GN based system of [PERSON] et al. [5] quantified by self-consistency using [PERSON]'s ratio. In our case, the camera resolution is larger (2048 pixel with \(61\times 61\) pixel per subset instead of 1024 pixel with \(41\times 41\)-pixel subsets in [5]) and the subpixel-resolution lower (0.02 pixel instead of 0.005) which  
\begin{table}
\begin{tabular}{c c c c c c c} \hline  & **Pan 2015** & **Pan 2016 [5]** & **Wang 2018** & **Wang 2018** & **Wang 2018** & **This,** & **This,** \\  & [33] & & [22] **Var. 2** & [22] **Var. 4** & **Strain-Contr.** & **Full-Field** \\ \hline Processor type & CPU & CPU & CPU + GPU & CPU + GPU & CPU + GPU & CPU + GPU \\ DIC algorithm & IC-GN & IC-GN & FFT-CC + & FFT-CC + & FFT-CC & FFT-CC \\ Path-dependent & yes & yes & yes & no & no & no \\ Maximum displacement & tracking & tracking & tracking & - & 97-pixel & 112-pixel \\ No of subsets & 29949 & 4 & 9440 & 100 & 8 & 2500 \\ Subset size \(n_{T}\) & 21-pixel & 41-pixel & 21-pixel & 21-pixel & 61-pixel & 31-pixel \\ Sampling rate & 1.46 Hz & 117 Hz & 30 Hz & 30 Hz & 1200 Hz & 10 Hz \\  & (0.24 Hz) & 44 kHz & & & & \\ Processing rate & (7.2 kHz) & 468 Hz & 283 kHz & 3 kHz & 9.6 kHz & 25 kHz \\ Latency & - & - & - & - & 2 ms & 100 ms \\ Marker-free & no & no & no & no & yes & yes \\ \hline \end{tabular}
\end{table}
Table 2: Performance comparison of different real-time 2D-DIC systems. Parameters marked with ‘-’ are not provided in the corresponding publication.  
might be an effect of the zero-order shape function. However, these values are not exactly comparable. Nevertheless, they give a hint because other references are hardly available.