Search results for "Quality inspection"

showing 6 items of 6 documents

Enabling robotic adaptive behaviour capabilities for new industry 4.0 automated quality inspection paradigms

2020

The seamless integration of industrial robotic arms with server computers, sensors and actuators can revolutionise the way in which automated non-destructive testing (NDT) is performed and conceived. Achieving effective integration and realising the full potential of robotic systems presents significant challenges, since robots, sensors and end-effector tools are often not necessarily designed to be put together and form a holistic system. This paper presents recent breakthroughs, opening up new scenarios for the inspection of product quality in advanced manufacturing. Many years of research have brought to software platforms the ability to integrate external data acquisition instrumentatio…

Industry 4.0Computer scienceTK0211 other engineering and technologies02 engineering and technology01 natural sciencesSettore ING-IND/14 - Progettazione Meccanica E Costruzione Di MacchineSoftware0103 physical sciencesMaterials ChemistryAutomated and robotic NDTAdvanced manufacturingMotion planning010301 acousticscomputer.programming_language021103 operations researchbusiness.industryMechanical EngineeringMetals and AlloysRobotics Quality Inspection Adaptive Industry 4.0Python (programming language)Industry 4.0ToolboxMechanics of MaterialsSystems engineeringAutonomous inspectionRobotbusinessRobotic armcomputer
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Application of deep convolutional neural networks for the detection of anthracnose in olives using VIS/NIR hyperspectral images

2021

Anthracnose is one of the primary diseases that affect olive production before and after harvest, causing severe damage and economic losses. The objective of this work is to detect this disease in the early stages, using hyperspectral images and advanced modelling techniques of Deep Learning (DL) and convolutional neural networks (CNN). The olives were artificially inoculated with the fungus. Hyperspectral images (450–1050 nm) of each olive were acquired until visual symptoms of the disease were observed, in some cases up to 9 days. The olives were classified into two classes: control, inoculated with water, and fungi composed of olives inoculated with the fungus. The ResNet101 architecture…

N01 Agricultural engineeringQuality inspectionqualitySpectral imagingU30 Research methodsFungiComputer visionH20 Plant diseasesOlea europaea
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Application of deep convolutional neural networks for the detection of anthracnose in olives using VIS/NIR hyperspectral images

2021

Abstract Anthracnose is one of the primary diseases that affect olive production before and after harvest, causing severe damage and economic losses. The objective of this work is to detect this disease in the early stages, using hyperspectral images and advanced modelling techniques of Deep Learning (DL) and convolutional neural networks (CNN). The olives were artificially inoculated with the fungus. Hyperspectral images (450–1050 nm) of each olive were acquired until visual symptoms of the disease were observed, in some cases up to 9 days. The olives were classified into two classes: control, inoculated with water, and fungi composed of olives inoculated with the fungus. The ResNet101 arc…

N01 Agricultural engineeringbusiness.industryDeep learningFungiHyperspectral imagingForestryPattern recognitionHorticultureBiologyVisual symptomsConvolutional neural networkComputer Science ApplicationsQuality inspectionSpectral imagingN20 Agricultural machinery and equipmentU30 Research methodsComputer visionArtificial intelligenceH20 Plant diseasesOlea europaeabusinessAgronomy and Crop ScienceComputers and Electronics in Agriculture
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Apparence des matériaux, Vision artificielle, Inspection qualité, Reflectance Transformation Imaging

2022

Mastering the visual perception of the surfaces of manufactured products is a central issue for industry. However, in industry, the quality of surfaces is often assessed by human inspectors. Only a few specific cases use an instrumental or photometric approach. Among the photometric approaches, one of them is experiencing significant growth: Reflectance Transformation Imaging (RTI). However, this technique has limitations in terms of data acquisition and processing. The objective is therefore to correct some of these limitations in order to improve the RTI and, consequently, the visual quality control of surface conditions in industry.The current RTI systems are limited and cannot meet our …

Quality Inspection[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingArtificial VisionReflectance Transformation ImagingApparence des matériauxInspection qualitéMaterial AppearanceVision artificielle
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HD-RTI: an adaptive multi-light imaging approach for the quality assessment of manufactured surfaces

2021

International audience; Reflectance Transformation Imaging (RTI) is a technique for estimating surface local angular reflectance from a set of stereo-photometric images captured with variable lighting directions. The digitization of this information fully fits into the industry 4.0 approach and makes it possible to characterize the visual properties of a surface. The proposed method, namely HD-RTI, is based on the coupling of RTI and HDR imaging techniques. This coupling is carried out adaptively according to the response at each angle of illumination. The proposed method is applied to five industrial samples which have high local variations of reflectivity because of their heterogeneity of…

Surface (mathematics)0209 industrial biotechnologyGeneral Computer ScienceComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyMachine visionSet (abstract data type)020901 industrial engineering & automationQuality (physics)[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingRobustness (computer science)0202 electrical engineering electronic engineering information engineeringComputer visionComputingMethodologies_COMPUTERGRAPHICSCouplingbusiness.industryQuality assessmentGeneral Engineering[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Variable (computer science)Quality inspection020201 artificial intelligence & image processingArtificial intelligenceMaterial AppearancebusinessPolynomial texture mapping
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Digitization and characterization of local reflectance of complex surfaces for visual inspection

2022

Mastering the visual perception of the surfaces of manufactured products is a central issue for industry. However, in industry, the quality of surfaces is often assessed by human inspectors. Only a few specific cases use an instrumental or photometric approach. Among the photometric approaches, one of them is experiencing significant growth: Reflectance Transformation Imaging (RTI). The RTI makes it possible to obtain a reduced and simplified estimate of the Bidirectional Reflectance Distribution Function (BRDF) and an estimate of the geometry of the surface. However, this technique has limitations in terms of data acquisition and processing. The objective is therefore to correct some of th…

Vision Artificielle[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH]Quality inspectionArtificial VisionReflectance Transformation ImagingApparence des matériauxInspection qualitéMaterial Appearance
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