Nothing Special   »   [go: up one dir, main page]

Hüthwohl et al., 2018 - Google Patents

Detecting healthy concrete surfaces

Hüthwohl et al., 2018

View PDF
Document ID
5772427043872565715
Author
Hüthwohl P
Brilakis I
Publication year
Publication venue
Advanced Engineering Informatics

External Links

Snippet

Teams of engineers visually inspect more than half a million bridges per year in the US and EU. There is clear evidence to suggest that they are not able to meet all bridge inspection guideline requirements due to a combination of the level of detail expected, the limited time …
Continue reading at www.repository.cam.ac.uk (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20112—Image segmentation details
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G06F17/5009—Computer-aided design using simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T1/00—General purpose image data processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K2209/19—Recognition of objects for industrial automation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management

Similar Documents

Publication Publication Date Title
Hüthwohl et al. Detecting healthy concrete surfaces
Hüthwohl et al. Multi-classifier for reinforced concrete bridge defects
Loverdos et al. Automatic image-based brick segmentation and crack detection of masonry walls using machine learning
Xu et al. Automatic defect detection and segmentation of tunnel surface using modified Mask R-CNN
Kalfarisi et al. Crack detection and segmentation using deep learning with 3D reality mesh model for quantitative assessment and integrated visualization
Wei et al. Instance-level recognition and quantification for concrete surface bughole based on deep learning
Wang et al. Autonomous damage segmentation and measurement of glazed tiles in historic buildings via deep learning
Tran et al. One stage detector (RetinaNet)-based crack detection for asphalt pavements considering pavement distresses and surface objects
Li et al. Automatic defect detection of metro tunnel surfaces using a vision-based inspection system
Safaei et al. An automatic image processing algorithm based on crack pixel density for pavement crack detection and classification
Zhang et al. Automatic pavement defect detection using 3D laser profiling technology
Zhao et al. A deep learning-based approach for refined crack evaluation from shield tunnel lining images
Sánchez-Rodríguez et al. Automated detection and decomposition of railway tunnels from Mobile Laser Scanning Datasets
Yang et al. Datasets and processing methods for boosting visual inspection of civil infrastructure: A comprehensive review and algorithm comparison for crack classification, segmentation, and detection
Loverdos et al. Geometrical digital twins of masonry structures for documentation and structural assessment using machine learning
Dang et al. Deep learning-based masonry crack segmentation and real-life crack length measurement
Guo et al. Monitoring and automatic characterization of cracks in strain-hardening cementitious composite (SHCC) through intelligent interpretation of photos
Pozzer et al. Effect of different imaging modalities on the performance of a CNN: An experimental study on damage segmentation in infrared, visible, and fused images of concrete structures
Panella et al. Deep learning and image processing for automated crack detection and defect measurement in underground structures
Li et al. Tunnel crack detection using coarse‐to‐fine region localization and edge detection
Situ et al. A transfer learning-based YOLO network for sewer defect detection in comparison to classic object detection methods
Guerrieri et al. Flexible and stone pavements distress detection and measurement by deep learning and low-cost detection devices
Ma et al. Complex texture contour feature extraction of cracks in timber structures of ancient architecture based on YOLO algorithm
Park et al. Learning‐based image scale estimation using surface textures for quantitative visual inspection of regions‐of‐interest
Li et al. Pixel-level detection and measurement of concrete crack using faster region-based convolutional neural network and morphological feature extraction