Prof. Rubén Usamentiaga Profile

Prof. Rubén Usamentiaga

Associate Professor at Univ de Oviedo

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Publications (14)

Proceedings Article | 14 May 2019 Paper

Defect detection based on monogenic signal processing

J. Fleuret, C. Ibarra-Castanedo, L. Lei, S. Sfarra, R. Usamentiaga, X. Maldague

Proceedings Volume 10986, 109861X (2019) https://doi.org/10.1117/12.2519087

KEYWORDS: Defect detection, Signal processing, Image processing, Thermography, Reconstruction algorithms, Neodymium, Infrared imaging, Infrared radiation, Detection theory, Signal analyzers

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SPIE Journal Paper | 3 January 2013

Software architecture for time-constrained machine vision applications

Rubén Usamentiaga, Julio Molleda, Daniel Garcia, Francisco Bulnes

JEI, Vol. 22, Issue 01, 013001, (January 2013) https://doi.org/10.1117/12.10.1117/1.JEI.22.1.013001

KEYWORDS: Computer architecture, Machine vision, Image processing, Human-machine interfaces, Cameras, Sensors, Image acquisition, Data processing, Data modeling, Visual process modeling

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Proceedings Article | 2 May 2012 Paper

A flexible software architecture for scalable real-time image and video processing applications

Rubén Usamentiaga, Julio Molleda, Daniel García, Francisco Bulnes

Proceedings Volume 8437, 843708 (2012) https://doi.org/10.1117/12.921397

KEYWORDS: Image processing, Computer architecture, Video processing, Data processing, Data modeling, Human-machine interfaces, Image acquisition, Computer programming, Sensors, Real time image processing

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Proceedings Article | 7 February 2011 Paper

Towards autonomic computing in machine vision applications: techniques and strategies for in-line 3D reconstruction in harsh industrial environments

Julio Molleda, Rubén Usamentiaga, Daniel García, Francisco Bulnes

Proceedings Volume 7877, 78770N (2011) https://doi.org/10.1117/12.872235

KEYWORDS: Machine vision, 3D modeling, Computing systems, Image processing, Image acquisition, Manufacturing, Cameras, Imaging systems, Inspection, Reconstruction algorithms

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Nowadays machine vision applications require skilled users to configure, tune, and maintain. Because such users are scarce, the robustness and reliability of applications are usually significantly affected. Autonomic computing offers a set of principles such as self-monitoring, self-regulation, and self-repair which can be used to partially overcome those problems. Systems which include self-monitoring observe their internal states, and extract features about them. Systems with self-regulation are capable of regulating their internal parameters to provide the best quality of service depending on the operational conditions and environment. Finally, self-repairing systems are able to detect anomalous working behavior and to provide strategies to deal with such conditions. Machine vision applications are the perfect field to apply autonomic computing techniques. This type of application has strong constraints on reliability and robustness, especially when working in industrial environments, and must provide accurate results even under changing conditions such as luminance, or noise. In order to exploit the autonomic approach of a machine vision application, we believe the architecture of the system must be designed using a set of orthogonal modules. In this paper, we describe how autonomic computing techniques can be applied to machine vision systems, using as an example a real application: 3D reconstruction in harsh industrial environments based on laser range finding. The application is based on modules with different responsibilities at three layers: image acquisition and processing (low level), monitoring (middle level) and supervision (high level). High level modules supervise the execution of low-level modules. Based on the information gathered by mid-level modules, they regulate low-level modules in order to optimize the global quality of service, and tune the module parameters based on operational conditions and on the environment. Regulation actions involve modifying the laser extraction method to adapt to changing conditions in the environment.

Proceedings Article | 25 January 2011 Paper

Parallel training and testing methods for complex image processing algorithms on distributed, heterogeneous, unreliable, and non-dedicated resources

Rubén Usamentiaga, Daniel García, Julio Molleda, Ignacio Sainz, Francisco Bulnes

Proceedings Volume 7872, 787205 (2011) https://doi.org/10.1117/12.872212

KEYWORDS: Image processing, Genetic algorithms, Detection and tracking algorithms, Edge detection, Algorithm development, Reliability, Testing and analysis, Optimization (mathematics), Pollution control, Image understanding

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SPIE Journal Paper | 1 October 2010

Real-time line scan extraction from infrared images using the wedge method in industrial environments

Rubén Usamentiaga, Julio Molleda, Daniel Garcia, Luis Perez, Guillermo Vecino

JEI, Vol. 19, Issue 04, 043017, (October 2010) https://doi.org/10.1117/12.10.1117/1.3514741

KEYWORDS: Infrared radiation, Infrared imaging, Temperature metrology, Calibration, Cameras, Infrared cameras, Hough transforms, Scanners, Thermography, Black bodies

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SPIE Journal Paper | 1 July 2010

Real-time flatness inspection of rolled products based on optical laser triangulation and three-dimensional surface reconstruction

Julio Molleda, Rubén Usamentiaga, Daniel García, Francisco Bulnes

JEI, Vol. 19, Issue 3, 031206, (July 2010) https://doi.org/10.1117/12.10.1117/1.3455987

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SPIE Journal Paper | 1 April 2009

Objective comparison of edge detection assessment methods based on genetic optimization

Rubén Usamentiaga, Daniel Garcia, Julio Molleda

JEI, Vol. 18, Issue 02, 023013, (April 2009) https://doi.org/10.1117/12.10.1117/1.3155514

KEYWORDS: Edge detection, Image segmentation, Detection and tracking algorithms, Image processing, Optimization (mathematics), Genetic algorithms, Lead, Genetics, Image processing algorithms and systems, Sensors

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SPIE Journal Paper | 1 January 2009

Automatic tuning for the segmentation of infrared images considering uncertain ground truth

Rubén Usamentiaga, Daniel Garcia, Julio Molleda

JEI, Vol. 18, Issue 01, 013001, (January 2009) https://doi.org/10.1117/12.10.1117/1.3059579

KEYWORDS: Image segmentation, Infrared imaging, Infrared radiation, Line scan image sensors, Image processing, Genetic algorithms, Fuzzy logic, Manufacturing, Edge detection, Convolution

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SPIE Journal Paper | 1 July 2008 Open Access

Real-time adaptive method for noise filtering of a stream of thermographic line scans based on spatial overlapping and edge detection

Rubén Usamentiaga, Daniel Garcia, Julio Molleda

JEI, Vol. 17, Issue 03, 033012, (July 2008) https://doi.org/10.1117/12.10.1117/1.2952844

KEYWORDS: Digital filtering, Image filtering, Temperature metrology, Edge detection, Line scan image sensors, Electronic filtering, Image processing, Interference (communication), Nonlinear filtering, Infrared radiation

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Proceedings Article | 26 February 2008 Paper

Real-time line scan extraction from infrared images using the wedge method in industrial environments

Rubén Usamentiaga, Daniel García, Julio Molleda

Proceedings Volume 6813, 68130R (2008) https://doi.org/10.1117/12.765579

KEYWORDS: Infrared radiation, Infrared imaging, Temperature metrology, Hough transforms, Calibration, Infrared cameras, Cameras, Black bodies, Thermography, Scanners

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Proceedings Article | 24 February 2005 Paper

Real-time system for flatness inspection of steel strips

Carlos Lopez, Daniel Garcia, Ruben Usamentiaga, Diego Gonzalez, Juan Gonzalez

Proceedings Volume 5679, (2005) https://doi.org/10.1117/12.585902

KEYWORDS: Cameras, Calibration, Optical fibers, Prototyping, Inspection, Manufacturing, Ranging, Optical simulations, Sensors, 3D modeling

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Proceedings Article | 18 May 2004 Paper

Real-time thermographic image acquisition and segmentation algorithms for continuous material

Ruben Usamentiaga, Daniel Garcia, Alberto Mijares, Juan Gonzalez

Proceedings Volume 5297, (2004) https://doi.org/10.1117/12.522061

KEYWORDS: Image segmentation, Line scan image sensors, Image processing, Sensors, Image processing algorithms and systems, Image filtering, Temperature metrology, Edge detection, Image acquisition, Calibration

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Proceedings Article | 4 April 2001 Paper

Shape inspection system with real-time adaptation to the luminance of the objects

Daniel Garcia, Ruben Usamentiaga, Ignacio Marin, Juan Gonzalez, Nicolas de Abajo

Proceedings Volume 4301, (2001) https://doi.org/10.1117/12.420914

KEYWORDS: Inspection, Cameras, Calibration, Head, Image processing, Feedback control, Imaging systems, Manufacturing, Computing systems, Infrared radiation

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Showing 5 of 14 publications

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