External visual interfaces for high precision measuring devices are based on the segmentation of images of their measuring reticle. In this paper, a method for subpixel straight lines detection is presented and tested on images taken from the reticle of a dark field autocollimator. The method has three steps, the sharpening of the image using a version of the Savitzky-Golay filter for smoothing and differentiation, the construction of a coarse edge image using Sobel filters, and finally, the subpixel edge location determination, by fitting a Gaussian function to orthogonal sections of the coarse edge image.We discuss results of applying the proposed method to images of the reticle of a Nikon 6D autocollimator, using the scale of the device as a benchmark for testing the error in the location of the lines and compare them with Sobel/Hough and Sobel/polynomial fitting. We report that for this type of image-content, Gaussian fitting has smaller uncertainty, when cameras with two different sensors are used.

/pdf/sub-pixel-straight-lines-detection-for-measuring-through-28gwtgm4k1.pdf

Sub-pixel straight lines detection for measuring through machine vision

In this paper a large size M-array based on pseudo-random numbers is proposed to implement spatial encoding structured light technique for dynamic 3D reconstruction. By using our technique, more accurate M-array can be generated. The large size M-array benefits in providing more information on object surfaces as more primitives can be contained in the pattern. We first discuss a pseudo-random array and point out problems existing ones. Then, we elaborate a new method to generate a large size M-array using pseudo-random numbers, which eliminates the limitation imposed on the coprime of rows and columns of pseudo-random array. To get more robust structured light system, color points are replaced with geometric symbols since color coded pattern are more sensitive to background and noise. The decoding method, in this research, is also improved, which significantly enhances accuracy of neighborhood finding in uneven or unbalance surfaces. Finally, 3D reconstruction results for cylinder and sculpture are presented to show the validity of the proposed large size M-array and decoding method.

A structured light vision measurement with large size M-array for dynamic scenes

According to examples of the presently disclosed subject matter, there is provided a system for estimating a source location of a projectile, comprising an optics an optics subsystem, a radar subsystem and a processor The processor is adapted to use range and velocity measurements obtained from data provided by the radar subsystem, a source direction and an event start time obtained from data provided by the optical subsystem and a predefined kinematic model for the projectile for estimating a range to a source location of the projectile

Estimating a source location of a projectile

Camera calibration represents a critical stage in visual measurement, directly impacting the measurement precision. Addressing the limitations of checkerboard and circular targets, resulting in low calibration accuracy and eccentricity errors, this study introduces a camera calibration method that relies on lightweight fan-shaped target detection and Fitness-Distance-Balance Chaotic Marine Predators Algorithm(FDBCMPA). Starting with the improvement of camera calibration targets by refining and designing fan-shaped targets, this paper aims to tackle eccentricity errors through hardware-based solutions. In the process of extracting target feature points, a lightweight object detection algorithm is devised to capture individual fan-shaped pattern positions from images, transitioning from global multi-shape feature detection to localized single-pattern feature extraction. This approach mitigates the distortions inherent in traditional checkerboard targets during global linear feature imaging and partially alleviates interference from background environments and similar features. Following the initial camera calibration, the FDBCMPA is employed to further optimize the calibration outcomes, thereby boosting the calibration method's performance. Experimental findings highlight that the enhanced object detection method in this study attains detection accuracy comparable to mainstream methods, with distinct advantages in detection speed, parameters, and FLOPs, rendering it more suitable for use in camera calibration. Additionally, the FDBCMPA demonstrates improvements in convergence results compared to MPA, PSO, TACPSO, Chimp, and other methods. The final camera calibration results demonstrate an impressive reprojection error of 0.0738 pixels through the utilization of the proposed camera calibration method introduced in this paper, and substantiate the practicality and effectiveness of the calibration method proposed in this study. 

Camera calibration based on lightweight fan-shaped target detection and fitness-distance-balance chaotic marine predators algorithm

The paper presents a new Automatic Waterjet Positioning Vision System (AWPVS) and investigates components of workpiece positioning accuracy. The main purpose of AWPVS is to precisely identify the position and rotation of a workpiece placed on a waterjet machine table. Two webcams form a basis for the system, and constitute its characteristics. The proposed algorithm comprises various image processing techniques to assure a required identification precision. To validate the PVS identification quality, synthetic images were applied under various conditions. The analysis ascertains dependence of an object detection rate and accuracy on a size of cropping frame. Experimental results of the proposed PVS prototype prove that a combination of the vision algorithm and webcams is an alternative to dedicated expensive industrial vision systems. The two main components of AWPVS uncertainty, a machine component and PSV component are discerned and estimated.

https://www.eejournal.ktu.lt/index.php/elt/article/view/5656/3061

An Analysis of Uncertainty and Robustness of Waterjet Machine Positioning Vision System

In order to improve the precision of camera calibration in the field of computer vision, we have to detect the points of the calibration pattern precisely. A new approach to sub-pixel corner detection of a grid is proposed in this paper, which is based on the combination of Hough Transform and least square fit. The procedure of the approach is as follows: (1) The image is divided into small regions to avoid the influence of camera lens distortion on linear fitting and each region has only one corner definitely. Edges of the grid in each region are detected by the Canny arithmetic operator. (2) Straight lines in each region are detected by Hough Transform. (3) Two straight lines with a certain separation angle are selected arbitrarily in each region as initial location. Then, edge-points are searched and recorded in the neighborhoods of each straight line in view of that the results of Hough Transform may not be sufficient for the edge location in practice. (4) Four straight lines are fitted by least square using the edge-points detected in each region. Center of the quadrilateral formed by the straight lines is calculated as the sub-pixel corner location. Finally, experimental results show that sub-pixel corner location of the grid can be obtained correctly and precisely, and none of them are missed. Consequently, it has been proved that this approach is feasible in the application of sub-pixel corner detection of a grid.

A novel approach to sub-pixel corner detection of the grid in camera calibration

Belonging to the dynamic and real-time metrology, the key on 3D shape measurement of moving object is one-shot technology including one image acquisition, real-time processing and displaying. According to different speeds of motion, a few structured light methods such as spatial encoding, FTP, phase shifting method and spacetime stereo are introduced and summarized in the form of principle, development, performance and application for shape acquisition of moving object in this paper. Although structured light for measuring 3D shape of moving object is significant and valuable in theory and engineering applications, the research still has some technological challenges and problems to be explored and solved.

3D shape acquisition of moving object based on structured light

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A novel approach to sub-pixel corner detection of the grid in camera calibration

3D shape acquisition of moving object based on structured light