Design and Detection Algorithm of White-Light Markers in Close-Range Photogrammetry

Chen, Z. P.; Lin, X. X.; Ling, Xuanzhe; Wang, Y.; Huang, Chan; Li, Z. W.; Sun, Zengguo

doi:10.1007/978-981-32-9441-7_68

Cited by 2 publications

(3 citation statements)

References 4 publications

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“…Feng et al [22] used a projected grid of white dots to reconstruct surface points of a flexible antenna. Chen et al [39] applied a pattern consisting of circular points in conjunction with encoded markers to measure the deformation of a crane girder. To detect and verify the projected markers, the authors of the presented applications employed common detection methods, as elaborated in Sect.…”

Section: Application Of Reference Projectionsmentioning

confidence: 99%

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Intelligent predetection of projected reference markers for robot-based inspection systems

Bauer

Schmitt

Dirr

et al. 2022

Prod. Eng. Res. Devel.

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Technical advancements in optical devices like sensors and projectors have led to tremendous innovations in manufacturing metrology, not least due to reductions in cost and the use of sophisticated image processing software. More recently, methods based on machine learning have demonstrated their high potential in meeting challenges that are difficult to overcome using conventional image processing techniques. In this context, we present an approach for the intelligent predetection of projected reference markers in robot-based inspection systems. These markers support the alignment of different sensor views and do not need to be physically attached to any parts. However, their robust detection is challenging under unfavorable lighting conditions. Hence, we introduce trained models of a cascade classifier based on both synthetic and real image data. Subsequently, we present the detection performance for different shapes and designs of markers projected onto real-world sheet metal parts as used in the automotive industry. The results demonstrate that properly trained classifiers can achieve a recall and precision of 90% and higher. The use of intelligent predetection promises more robust results in the subsequent detection of projected markers and, thus, benefits image processing in particular in geometric quality assurance applications.

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Section: Application Of Reference Projectionsmentioning

confidence: 99%

“…To detect and verify the projected markers, the authors of the presented applications employed common detection methods, as elaborated in Sect. 2.1, albeit individual thresholds were selected by hand [4], ambient light was controlled [22], or complex routines were needed to eliminate false marker candidates [39].…”

Section: Application Of Reference Projectionsmentioning

confidence: 99%

Intelligent predetection of projected reference markers for robot-based inspection systems

Bauer

Schmitt

Dirr

et al. 2022

Prod. Eng. Res. Devel.

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“…The advent of computer technology has facilitated computers' applications in analytical calculations, theoretical rendezvous, and establishing covariances between image points and feature points. This advancement fosters a plethora of analytical algorithms designed to determine the information pertinent to the object to be photographed, such as shape, size, spatial location, texture, and color [23,24]. Alameda-Hernandez et al [25] used the spatial backward/forward rendezvous method in combination with image resolution to assess the slope stability of a weak foliated rocky slope in Andalusia, Spain.…”

Section: Introductionmentioning

confidence: 99%

Methods and research for deformation monitoring of earth and rock dams based on close-range photogrammetry

Wang,

Cheng,

Xiong

et al. 2024

Meas. Sci. Technol.

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Traditional means of monitoring deformation in earth and rock dams encounter challenges such as low monitoring efficiency and limited coverage. Despite the potential of emerging technologies such as GPS and three-dimensional laser scanning, their adoption is expensive and hard to promote. This paper presents a deformation monitoring method for earth and rock dams based on the close-range photogrammetry technique. The proposed approach focuses on analytical algorithm the design and deployment of monitoring points, photographic schemes, camera checking and calibration, as well as deformation analysis methods. Initially, based on the analysis of the parsing algorithms’ applicability, they are fused to address the shortcomings of common image parsing methods in meeting the requirements of high precision and multi-image processing for deformation monitoring of earth and rock dams. Subsequently, the fused algorithm is introduced to analyze the acquired image data for 3D reconstruction, and the deformation in earth and rock dams is assessed based on the generated dense point cloud model. The proposed deformation monitoring method is applied to Pine Bridge Reservoir Dam, and the results demonstrated its capacity to comprehensively analyze the deformation. Furthermore, the required equipment is simple and easy to operate, aligning with the requirements for deformation monitoring accuracy of earth and rock dams.

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Design and Detection Algorithm of White-Light Markers in Close-Range Photogrammetry

Cited by 2 publications

References 4 publications

Intelligent predetection of projected reference markers for robot-based inspection systems

Intelligent predetection of projected reference markers for robot-based inspection systems

Methods and research for deformation monitoring of earth and rock dams based on close-range photogrammetry

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