A robust and accurate sub-pixel extraction methodof laser stripe in complex circumstances

AbstractThis study presents laser stripe center extraction algorithm for desktop-level 3D laser scanners. The laser stripe center extraction accuracy is an important factor affecting 3D scanning result. Desktop-level devices should have adaptability of a wide range of scanning objects. In this paper, laser stripe energy distribution characteristics with different laser stripe width, ambient light, materials and colors are obtained by experiments. Experiment results show that waveforms of bright spot, low brightness stripe and stripe with large width are complex or easily disturbed, so the center extraction algorithm of them are studied. The extraction effects of extremum method, gradient method and gray centroid method under different conditions are compared. Based on traditional grayscale value, a weighted grayscale value is proposed to extract laser stripe center. Standard deviations of extracted pixel position and fitting pixel position are calculated by different method with different weighted grayscale value. For different conditions, especially for different ambient light intensity, weight matrix plays an important role to extraction result.

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A real time detection method for abnormal strapping of steel coil based on CCD active imaging

Measurement Science and Technology ◽

10.1088/1361-6501/ac3856 ◽

2021 ◽

Author(s):

Chuan Ye ◽

Liming Zhao ◽

Qiyan Wang ◽

Bo Pan ◽

Youchun Xie ◽

...

Keyword(s):

Maximum Entropy ◽

Detection Method ◽

Saliency Detection ◽

Automatic Segmentation ◽

Engineering Application ◽

Detection Accuracy ◽

Steel Coil ◽

Detection Model ◽

Laser Stripe ◽

Active Imaging

Abstract In order to accurately detect the abnormal looseness of strapping in the process of steel coil hoisting, an accurate detection method of strapping abnormality based on CCD structured light active imaging is proposed. Firstly, a maximum entropy laser stripe automatic segmentation model integrating multi-scale saliency features is constructed. With the help of saliency detection model, the purpose is to reduce the interference of the environment to the laser stripe and highlight the distinguishability between the stripe and the background. Then, the maximum entropy is used to segment the fused saliency features and accurately extract the stripe contour. Finally, the stripe normal field is obtained by calculating the stripe gradient vector, the stripe center line is extracted based on the stripe distribution normal direction, and the abnormal strapping is recognized online according to the stripe center. Experiments show that the proposed method is effective in terms of detection accuracy and time efficiency, and has certain engineering application value.

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Real-Time Sensing of Sag Geometry During GTA Welding

Journal of Manufacturing Science and Engineering ◽

10.1115/1.2831090 ◽

1997 ◽

Vol 119 (2) ◽

pp. 151-160 ◽

Cited By ~ 38

Author(s):

Y. M. Zhang ◽

R. Kovacevic

Keyword(s):

Real Time ◽

Vision System ◽

Structured Light ◽

Gta Welding ◽

Seam Tracking ◽

Image Processing Algorithm ◽

3D Vision ◽

Full Penetration ◽

Laser Stripe ◽

Penetration Control

Seam tracking and weld penetration control are two fundamental issues in automated welding. Although the seam tracking technique has matured, the latter still remains a unique unsolved problem. It was found that the full penetration status during GTA welding can be determined with sufficient accuracy using the sag depression. To achieve a new full penetration sensing technique, a structured-light 3D vision system is developed to extract the sag geometry behind the pool. The laser stripe, which is the intersection of the structured-light and weldment, is thinned and then used to acquire the sag geometry. To reduce possible control delay, a small distance is selected between the pool rear and laser stripe. An adaptive dynamic search for rapid thinning of the stripe and the maximum principle of slope difference for unbiased recognition of sag border were proposed to develop an effective real-time image processing algorithm for sag geometry acquisition. Experiments have shown that the proposed sensor and image algorithm can provide reliable feedback information of sag geometry for the full penetration control system.

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