Dr. Rico Nestler Profile

Dr. Rico Nestler

at Technische Univ Ilmenau

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Publications (6)

Proceedings Article | 9 August 2023 Presentation + Paper

Investigation on automated visual SMD-PCB inspection based on multimodal one-class novelty detection

Zheng Liu, Qichao Wang, Rico Nestler, Gunther Notni

Proceedings Volume 12621, 1262110 (2023) https://doi.org/10.1117/12.2673602

KEYWORDS: Feature fusion, Inspection, Data fusion, Defect detection

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Proceedings Article | 7 August 2023 Paper

Single-shot structured light with diffractive optic elements for real-time 3D imaging in collaborative logistic scenarios

Darko Vehar, Andreas Hermerschmidt, Rico Nestler, Karl-Heinz Franke

Proceedings Volume 12624, 126240V (2023) https://doi.org/10.1117/12.2675818

KEYWORDS: Projection systems, Cameras, Structured light, Diffractive optical elements, Calibration, Content addressable memory, 3D image processing, Imaging systems, 3D metrology, Binary data

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We introduce an innovative concept for 3D imaging that utilizes a structured light principle. While our design is specifically tailored for collaborative scenarios involving mobile transport robots, it is also applicable to similar contexts. Our system pairs a standard camera with a projector that employs a diffractive optical element (DOE) and a collimated laser beam to generate a coded light pattern. This allows a three-dimensional measurement of objects from a single camera shot. The main objective of the 3D-sensor is to facilitate the development of automatic, dynamic and adaptive logistics processes capable of managing diverse and unpredictable events. The key novelty of our proposed system for triangulation-based 3D reconstruction is the unique coding of the light pattern, ensuring robust and efficient 3D data generation, even within challenging environments such as industrial settings. Our pattern relies on a perfect submap, a matrix featuring pseudorandomly distributed dots, where each submatrix of a fixed size is distinct from the others. Based on the size of the working space and known geometrical parameters of the optical components, we establish vital design constraints like minimum pattern size, uniqueness window size, and minimum Hamming distance for the design of an optimal pattern. We empirically examine the impact of these pattern constraints on the quality of the 3D data and compare our proposed encoding with some single-shot patterns found in existing literature. Additionally, we provide detailed explanations on how we addressed several challenges during the fabrication of the DOE, which are crucial in determining the usability of the application. These challenges include reducing the 0th diffraction order, accommodating a large horizontal field of view, achieving high point density, and managing a large number of points. Lastly, we propose a real-time processing pipeline that transforms an image of the captured dot pattern into a high-resolution 3D point cloud using a computationally efficient pattern decoding methodology.

Proceedings Article | 12 April 2021 Presentation + Paper

The evaluation of CUDA performance on the Jetson Nano board for an image binarization task

Febby Purnama Madrin, Maik Rosenberger, Rico Nestler, Paul-Gerald Dittrich, Gunther Notni

Proceedings Volume 11736, 117360G (2021) https://doi.org/10.1117/12.2586650

KEYWORDS: Image processing, Video processing, Video acceleration, Video, Real time image processing, GPU based image processing

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Proceedings Article | 17 September 2019 Open Access

Scene based camera pose estimation in Manhattan worlds

Darko Vehar, Rico Nestler, Karl-Heinz Franke

Proceedings Volume 11144, 111440L (2019) https://doi.org/10.1117/12.2530875

KEYWORDS: Cameras, Image segmentation, Calibration, Imaging systems, 3D modeling, Image processing, Sensors, Image analysis

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Proceedings Article | 17 September 2019 Open Access

Efficient 3D object tracking approach based on convolutional neural network and Monte Carlo algorithms used for a pick and place robot

Y. Zhang, C. Zhang, R. Nestler, M. Rosenberger, G. Notni

Proceedings Volume 11144, 1114414 (2019) https://doi.org/10.1117/12.2530333

KEYWORDS: 3D image processing, Convolutional neural networks, Monte Carlo methods, Evolutionary algorithms, Image processing, Particle filters, Neural networks, Image segmentation, Intelligent robotic vision

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Proceedings Article | 22 May 2009 Paper

Kelvin probe force microscopy: measurement data reconstruction

Torsten Machleidt, Erik Sparrer, Tim Kubertschak, Rico Nestler, Karl-Heinz Franke

Proceedings Volume 7378, 73781C (2009) https://doi.org/10.1117/12.821787

KEYWORDS: Point spread functions, Deconvolution, Scanning probe microscopy, Microscopy, Convolution, Microscopes, Data modeling, Chemical elements, Image processing, Analytical research

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Showing 5 of 6 publications

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