Stud Pose Detection Based on Photometric Stereo and Lightweight YOLOv4

There are hundreds of welded studs in a car. The posture of a welded stud determines the quality of the body assembly thus affecting the safety of cars. It is crucial to detect the posture of the welded studs. Considering the lack of accurate method in detecting the position of welded studs, this paper aims to detect the weld stud’s pose based on photometric stereo and neural network. Firstly, a machine vision-based stud dataset collection system is built to achieve the stud dataset labeling automatically. Secondly, photometric stereo algorithm is applied to estimate the stud normal map which as input is fed to neural network. Finally, we improve a lightweight YOLOv4 neural network which is applied to achieve the detection of stud position thus overcoming the shortcomings of traditional testing methods. The research and experimental results show that the stud pose detection system designed achieves rapid detection and high accuracy positioning of the stud. This research provides the foundation combining the photometric stereo and deep learning for object detection in industrial production.

Research on Character Computer Intelligent Recognition of Automobile Front Bar Bracket Based on Machine Vision

Aiming at the problem that the characters in the superimposed character area on the surface of the front bumper bracket of the car are difficult to recognize, a machine vision-based automobile front bumper bracket character recognition method is proposed, use Python, OpenCV and Halcon computer vision library for software system design. For eight images collected from different angles of light source directions, an innovative method of polynomial fitting gray value can reducethe uneven illumination of the images. The photometric stereo algorithm is used to obtain a high-contrast character image, and the separation of the two types of characters is simultaneously achieved. After the image filtering, opening and closing processes canremove background interference, use a morphological improvement algorithm based on scanning algorithm to complete character positioning, and then the improved algorithm of projection dichotomy based on the connected domain size is used to complete the character segmentation, and finally the support vector machine is used for character feature recognition. The experimental results claim that these methods can quickly separate superimposed characters and complete the recognition of non-color difference convex characters and inkjet characters, and the average recognition accuracy rate is over 96%, which meets the expected recognition requirements.

Real-time stereo semi-global matching for video processing using previous incremental information

This paper presents an incremental stereo algorithm designed to calculate a real-time disparity image. The algorithm is designed for stereo video sequences and uses previous information to reduce computation time and improve disparity image quality. It is based on the semi-global matching stereo algorithm but modified to reuse previous calculation information. Storing and reusing this information not only reduces computation time but improves accuracy in a cost filtering scheme. Some tests are presented to compare the computation time and results of the algorithm, which show that it can achieve better results in terms of quality and time than standard algorithms for some scenarios.

A Multi-view Camera Model for Line-Scan Cameras with Telecentric Lenses

We propose a novel multi-view camera model for line-scan cameras with telecentric lenses. The camera model supports an arbitrary number of cameras and assumes a linear relative motion with constant velocity between the cameras and the object. We distinguish two motion configurations. In the first configuration, all cameras move with independent motion vectors. In the second configuration, the cameras are mounted rigidly with respect to each other and therefore share a common motion vector. The camera model can model arbitrary lens distortions by supporting arbitrary positions of the line sensor with respect to the optical axis. We propose an algorithm to calibrate a multi-view telecentric line-scan camera setup. To facilitate a 3D reconstruction, we prove that an image pair acquired with two telecentric line-scan cameras can always be rectified to the epipolar standard configuration, in contrast to line-scan cameras with entocentric lenses, for which this is possible only under very restricted conditions. The rectification allows an arbitrary stereo algorithm to be used to calculate disparity images. We propose an efficient algorithm to compute 3D coordinates from these disparities. Experiments on real images show the validity of the proposed multi-view telecentric line-scan camera model.

Source apportionment of atmospheric mercury in the remote marine atmosphere: Mace Head GAW station, Irish western coast

We examined recent atmospheric mercury concentrations measured with a high temporal resolution of 15 min at Mace Head, a GAW station on the western coast of Ireland. We attributed a direct contribution of 34 % (0.44 ng m−3) to primary sources. Additionally, a steep decline (0.05 ng yr−1) in mercury concentrations was observed between 2013 and 2018. Using a stereo algorithm we reconstructed 99.9 % of the atmospheric mercury. A conservative analysis demonstrated no decrease in total gaseous mercury (TGM) associated with atmospheric species typically used as tracers for oceanic emissions. The results show that the atmospheric mercury mass is mainly loaded in a baseline factor with an ongoing decline. Moreover, we exploit temporal variation and wind pattern effects in the measured atmospheric species; the results show that the diurnal variation and seasonality in TGM observed in Mace Head are closely related to other species linked to primary sources and can be explained by transport from continental areas.

Source apportionment of atmospheric mercury in the remote marine atmosphere: Mace Head GAW station, Irish west coast

We examined recent atmospheric mercury concentrations measured with a high temporal resolution of 15 min. at Mace Head, a GAW station on the west coast of Ireland. We attributed a direct contribution of 34 % (0.44 ng m−3) to primary sources. Additionally, a steep decline (0.05 ng year−1) in mercury concentrations was observed between 2013 and 2018. Using a stereo algorithm we reconstructed 99.9 % of the atmospheric mercury. A conservative analysis demonstrated no decreasing of TGM associated with atmospheric species typically used as tracers for oceanic emissions. The results show that the atmospheric mercury mass is mainly loaded in a baseline factor with an on-going decline. Moreover, we exploit temporal variation and wind pattern effects in the measured atmospheric species, the results show that the diurnal variation and seasonality in TGM observed in Mace Head is closely related to other species linked to primary sources and can be explained by transport from continental areas.

An Efficient Implementation of a Census-Based Stereo Matching and Its Applications in Medical Imaging

Compared to most conventional efficient stereo matching algorithms that based on NCC (Normalized Cross-Correlation) or SAD (Sum of Absolute Difference), stereo matching based on census transform is robust to radiometric distortion. Thus, in the paper we propose a census-based efficient implementation stereo algorithm for medical imaging. Firstly, census-based stereo matching is investigated, and its specific implementation process is analyzed in detail. Secondly, in order to simplify the calculation process and improve the efficiency, the moving window and memory organization optimized techniques are used. The program runs on standard PC hardware utilizing various SSE2 instructions. Finally, stereo matching of four standard image pairs on the Middlebury image datasets and a paired cervical images obtained from clinical colposcope are implemented in an efficient way. The experimental results on simulated and real medical images prove the effectiveness of the method for the computational cost.