A known technique to obtain subpixel resolution by using object tracking through cross-correlation consists of interpolating the obtained correlation function and then refining peak location. Although the technique provides accurate results, peak location is usually biased toward the closest integer coordinate. This effect is known as the peak-locking error and it strongly limits this calculation technique’s experimental accuracy. This error may differ depending on the scene and algorithm used to fit and interpolate the correlation peak, but in general, it may be attributed to a sampling problem and the presence of aliasing. Many studies in the literature analyze this effect in the Fourier domain. Here, we propose an alternative analysis on the spatial domain. According to our interpretation, the peak-locking error may be produced by a non-symmetrical sample distribution, thus provoking a bias in the result. According to this, the peak interpolant function, the size of the local domain and low-pass filters play a relevant role in diminishing the error. Our study explores these effects on different samples taken from the DIC Challenge database, and the results show that, in general, peak fitting with a Gaussian function on a relatively large domain provides the most accurate results.

The COVID pandemic is forcing the renewal of scientific conferences, offering opportunities to introduce technological and inclusive developments. Our analysis focuses on the implementation of inclusive practices for female and early-career researchers in a virtual scientific conference. This organization approach was applied in the XIII Spanish Optical Meeting (RNO2021), which was also characterized by avatars interacting in an online metaverse. The effectiveness of inclusive policies and novel technological tools was evaluated using the participation data and a post-conference survey. Our study reveals the high impact of inclusive actions and a strong interest in the scientific community to explore conference advances.

Many applications in physics and engineering require non-invasive, precise object tracking, which can be achieved with image processing methods at very good cost-efficiency ratios. The traditional method for measuring displacement with subpixel resolution involves cross-correlation between images and interpolation of the correlation peak. While this method enables target tracking with a resolution of thousandths of a pixel, it is computationally intensive and susceptible to peak-locking errors. Recently, a new method based on discrete subtraction between images has been presented as an alternative to cross-correlation to improve computational efficiency, which also results in being free of peak-locking errors. This manuscript presents an experimental evaluation of the performance of the discrete subtraction method (DSM) and compares it with the cross-correlation method in terms of subpixel accuracy and deviation errors. Four different targets were used with apparent displacements as small as 0.002 px, which approaches the theoretical digital resolution limit. The results show that the discrete subtraction method is more sensitive to noise but does not suffer from peak-locking error, thus being a reliable alternative to the correlation method, mainly for calibration processes.

Some materials undergo hygric expansion when soaked. In porous rocks, this effect is enhanced by the pore space, because it allows water to reach every part of its volume and to hydrate most swelling parts. In the vicinity, this enlargement has negative structural consequences as adjacent elements support some compressions or displacements. In this work, we propose a normalized cross-correlation between rock surface texture images to determine the hygric expansion of such materials. We used small porous sandstone samples (11 × 11 × 30 mm³) to measure hygric swelling. The experimental setup comprised an industrial digital camera and a telecentric objective. We took one image every 5 min for 3 h to characterize the whole swelling process. An error analysis of both the mathematical and experimental methods was performed. The results showed that the proposed methodology provided, despite some limitations, reliable hygric swelling information by a non-contact methodology with an accuracy of 1 micron and permitted the deformation in both the vertical and horizontal directions to be explored, which is an advantage over traditional linear variable displacement transformers.

The use of natural targets is one of the obstacles to the extensive use of digital image cross-correlation for measuring movements in civil structures. Long distance measurement through image and without access to the structure itself, brings results in an improvement in accessibility, being the procedure cheaper and safer than common methods that require direct access to the measuring point. One of the most used materials in construction is concrete. Therefore, it is important to analyze its performance when using image cross-correlation. In this work, we have made a series of concrete probes with different production characteristics to have a representative variety of concrete surfaces. With them, we have studied their floor error in a cross-correlation procedure using different illumination and blur conditions, to evaluate the influence of those parameters on the results. All results are compared to those obtained using the conventional texture for image cross-correlation techniques, that is a pseudo-speckle target. All experiments are done in laboratory conditions to control all variables involved and to avoid the influence of other variables linked to open air conditions, such as atmospheric disturbances. As a result, we have determined the best conditions to use the natural concrete texture and we have quantified that using this texture leads to a decrease in the accuracy of the results from two to three times the one obtained with a typical pseudo-speckle texture.