[go: up one dir, main page]

Ren et al., 2022 - Google Patents

State of the art in defect detection based on machine vision

Ren et al., 2022

View HTML
Document ID
8128999273420313759
Author
Ren Z
Fang F
Yan N
Wu Y
Publication year
Publication venue
International Journal of Precision Engineering and Manufacturing-Green Technology

External Links

Snippet

Abstract Machine vision significantly improves the efficiency, quality, and reliability of defect detection. In visual inspection, excellent optical illumination platforms and suitable image acquisition hardware are the prerequisites for obtaining high-quality images. Image …
Continue reading at link.springer.com (HTML) (other versions)

Classifications

    • 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
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G06T7/001—Industrial image inspection using an image reference approach
    • 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
    • G06T2207/30148—Semiconductor; IC; Wafer
    • 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
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • 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
    • G06T2207/10024—Color image
    • 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
    • G01N21/89—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles
    • 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
    • G06K9/20—Image acquisition
    • 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
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • 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
    • 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
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image

Similar Documents

Publication Publication Date Title
Ren et al. State of the art in defect detection based on machine vision
Tang et al. Review of surface defect detection of steel products based on machine vision
Mordia et al. Visual techniques for defects detection in steel products: A comparative study
Zheng et al. Recent advances in surface defect inspection of industrial products using deep learning techniques
Yang et al. Real-time tiny part defect detection system in manufacturing using deep learning
CN111415329B (en) A method for detecting surface defects of workpieces based on deep learning
Xue et al. A fast detection method via region‐based fully convolutional neural networks for shield tunnel lining defects
Kuo et al. Automated optical inspection system for surface mount device light emitting diodes
Xue-Wu et al. A vision inspection system for the surface defects of strongly reflected metal based on multi-class SVM
CN113592845A (en) Defect detection method and device for battery coating and storage medium
CN115908354B (en) A photovoltaic panel defect detection method based on dual-scale strategy and improved YOLOV5 network
Sun et al. Unsupervised surface defect detection of aluminum sheets with combined bright-field and dark-field illumination
Zuo et al. Classifying cracks at sub-class level in closed circuit television sewer inspection videos
Guo et al. Detection and classification of pipe defects based on pipe-extended feature pyramid network
CN116612106A (en) A method for surface defect detection of optical components based on YOLOX algorithm
Qiao et al. A Review of Metal Surface Defect Detection Technologies in Industrial Applications
Wei et al. Surface defects detection of cylindrical high-precision industrial parts based on deep learning algorithms: A review
Zhou et al. Surface defect detection of steel plate based on SKS-YOLO
Hao et al. An image-based hairline crack identification method for metal parts
Singh et al. Segmentation technique for the detection of Micro cracks in solar cell using support vector machine
Jin et al. Outer surface defect detection of steel pipes with 3D vision based on multi-line structured lights
Yang et al. Brake disc defect detection method based on an improved multi-scale template matching algorithm
Lang et al. Virtual-sample-based defect detection algorithm for aluminum tube surface
CN119784741A (en) A training method and system for 5G flexible circuit board defect detection model
CN119991544A (en) Intelligent classification method and system for transmission line tension clamp defects based on two-dimensional images