Rendering for machine vision prototyping

Reiner, Jacek

doi:10.1117/12.802717

Cited by 8 publications

(8 citation statements)

References 2 publications

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“…Mohammadikaji [2] and Reiner [10] tackled with realistic image synthesis for machine vision inspection systems. Mohammadikaji coupled ray tracing with Fourier optics methods for introducing wave optics effects.…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, this approach lacks generality. Reiner [10] proposed more general simulation approach but lacks clear pipeline.…”

Section: Related Workmentioning

confidence: 99%

“…CGI techniques such as [21], [22], [23], [24] are commonly used for generation of photo-realistic images and are capable of producing remarkable results. However, their practical use in the field of surface inspection is minimal [2], [10]. We assume that the explanation lies in the following reasons.…”

Section: Requirements Analysismentioning

confidence: 99%

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Image Synthesis Pipeline for Surface Inspection

Bosnar¹,

Saric²,

Dutta³

et al. 2020

Preprint

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Surface inspection development requires large amounts of image data representing the inspected product surface. The image data should contain both the ideal surface and the defective surface that can appear during production. Although image synthesis comes as a natural solution to this problem, its application is not straightforward in automated surface inspection environments. The reason for that is a lot of manual work that should be done for creating defects, simulating the inspection environment, and setting up the acquisition system for validation of simulation. To address these issues, we present a novel pipeline that automatizes surface defect creation, provides realistic rendering in a predefined inspection environment setup, and an acquisition system that enables comparison with the real images. The pipeline creates geometry-imprinted defects which combined with physically based rendering methods enable realistic light response for different light and camera positions during image synthesis. Finally, synthesized images can becompared with the real image taken in the same setup enabling verification. Also, synthesized images enable the visualization of visible surfaces and defects for a given inspection plan.

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Section: Related Workmentioning

confidence: 99%

“…Therefore, this approach lacks generality. Reiner [10] proposed more general simulation approach but lacks clear pipeline.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Image Synthesis Pipeline for Surface Inspection

Bosnar¹,

Saric²,

Dutta³

et al. 2020

Preprint

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“…During the measurements dark field as well as backlight illumination was used. Both of this method allow enhancing contrast of the edges of imaging object such as powder stream [13] and therefore permit quantitative characterization of powder stream from cladding nozzle. Furthermore, on the basis of illumination, the spatial distribution of the powder can be determined with the image processing (segmentation, edge detection).…”

Section: Powder Concentration Measurementmentioning

confidence: 99%

Thermal imaging of laser powder interaction zone in Ultra-High Speed Laser Cladding process

Koruba¹,

Reiner²

2018

Proceedings of the 2018 International Conference on Quantitative InfraRed Thermography

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Laser cladding process is a coating deposition technology, where the layer of additional material is cladded due to interaction of powder particles with laser heat source and melt pool. The monitoring of interaction between laser beam and powder became more vital in specific Ultra-High Speed Laser Cladding process, since the cladding speed requires particles to be melted before reaching the substrate. Therefore, this paper presents the preliminary study of lateral measurement of powder concentration under the cladding nozzle and its temperature distribution during the process. Moreover, the evaluation of used spectral bands for observation of laser-powder interaction was carried out.

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“…Different aspects of such a simulation system were also subject of related work, e.g. Reiner et al (2008) focused on modeling different real world luminainares, Chessa et al (2011) proposed a system for creation of synthetic ground truth data for stereo vision systems using virtual reality technology. In contrast to this related work, our work mainly deals with modeling the reflectance properties of materials as good as possible by using the methods described in Section 2.2.…”

Section: Synthetic Ground Truth Data For Machine Vision Applicationsmentioning

confidence: 99%