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

Wu et al., 2021 - Google Patents

Surface crack detection based on image stitching and transfer learning with pretrained convolutional neural network

Wu et al., 2021

View PDF
Document ID
16748334640855416350
Author
Wu L
Lin X
Chen Z
Lin P
Cheng S
Publication year
Publication venue
Structural Control and Health Monitoring

External Links

Snippet

During the operating lifecycle of civil structures, cracks will occur inevitably, which may pose great threat to the safety of the structures without timely maintenance. Digital image processing techniques have great potential in automatically detecting cracks, which can …
Continue reading at onlinelibrary.wiley.com (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0004Industrial image inspection
    • G06T7/001Industrial image inspection using an image reference approach
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30108Industrial image inspection
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • G06K9/4604Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10024Color image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T1/00General purpose image data processing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K2209/00Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints

Similar Documents

Publication Publication Date Title
Wu et al. Surface crack detection based on image stitching and transfer learning with pretrained convolutional neural network
Xue et al. A fast detection method via region‐based fully convolutional neural networks for shield tunnel lining defects
Ni et al. Zernike‐moment measurement of thin‐crack width in images enabled by dual‐scale deep learning
Ali et al. Structural crack detection using deep convolutional neural networks
Xu et al. Surface fatigue crack identification in steel box girder of bridges by a deep fusion convolutional neural network based on consumer-grade camera images
Ni et al. Pixel‐level crack delineation in images with convolutional feature fusion
Xing et al. A convolutional neural network-based method for workpiece surface defect detection
Dorafshan et al. Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete
Liu et al. Computer vision-based concrete crack detection using U-net fully convolutional networks
Li et al. Automatic pixel‐level multiple damage detection of concrete structure using fully convolutional network
Qiu et al. Automatic visual defects inspection of wind turbine blades via YOLO-based small object detection approach
Rezaie et al. Comparison of crack segmentation using digital image correlation measurements and deep learning
Alipour et al. Robust pixel-level crack detection using deep fully convolutional neural networks
Wu et al. Pruning deep convolutional neural networks for efficient edge computing in condition assessment of infrastructures
Golding et al. Crack detection in concrete structures using deep learning
Miao et al. Pixel‐level multicategory detection of visible seismic damage of reinforced concrete components
Fan et al. Use of parallel ResNet for high-performance pavement crack detection and measurement
Deng et al. Vision based pixel-level bridge structural damage detection using a link ASPP network
Chen et al. An automatic defect detection system for petrochemical pipeline based on cycle-gan and yolo v5
Li et al. Automatic bridge crack identification from concrete surface using ResNeXt with postprocessing
Quqa et al. Two-step approach for fatigue crack detection in steel bridges using convolutional neural networks
Yuan et al. Near real‐time bolt‐loosening detection using mask and region‐based convolutional neural network
Nsengiyumva et al. Critical insights into the state‐of‐the‐art NDE data fusion techniques for the inspection of structural systems
Han et al. Multispectral water leakage detection based on a one-stage anchor-free modality fusion network for metro tunnels
Geetha et al. Fast identification of concrete cracks using 1D deep learning and explainable artificial intelligence-based analysis