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.

Thermal effects in digital cameras can introduce measurable errors in high-precision optical systems, particularly where subpixel accuracy is required. This study analyzes self-heating effects in an industrial CMOS camera over a six-hour period, focusing on image drift and local distortions. Two configurations were evaluated: standard operation and operation with a passive aluminum heatsink. Using a fixed dot-pattern target, centroid tracking, and Zernike polynomial analysis, we quantified both global shifts and local deformations in the image plane. Results show that self-heating causes drift of up to one pixel during the first 90 min of operation. The heatsink reduced the stabilized temperature by nearly 20 °C, lowered the dark current by a factor of 20, and diminished drift and distortion, though not entirely. After thermal stabilization, residual errors remained below 0.1 pixels, enabling reliable subpixel measurements. These findings highlight the need for thermal management and mechanical stability in metrology-grade imaging setups and demonstrate that wavefront-inspired analysis methods are powerful tools for characterizing thermal distortions.

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.

Here we include a dataset of 86 pictures of concrete textures. The numerical name codifies the texture according to he following parameters:(First digit: Slump) Primer dígito: Consistencias: (First digit: Slump) - "s": Seco -- 1 (range [0-25] mm) - "p": Plástico -- 2 (range [25-50] mm) - "b": Blanda -- 3 (range [50-90] mm) - "f": Fluida -- 4 (range [90-150] mm) Segundo dígito: Método de fabricación: (Second digit: Compaction method) - "p": Pica -- 1 (ramming with a steel bar) - "m": Maza -- 2 (tapping with a rubber mallet) - "v": Vibrador -- 3 (electric vibrator) Tercer dígito: Material del encofrado: (Third digit: Formwork material) - "m": Madera -- 1 (wood) - "a": Acero -- 2 (steel)

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.