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Jehle et al., 2014 - Google Patents

Optimal lighting for defect detection: illumination systems, machine learning, and practical verification

Jehle et al., 2014

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Document ID
10088591217093160810
Author
Jehle M
Jähne B
Publication year
Publication venue
Forum Bildverarbeitung

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Snippet

We propose a novel approach for defect detection based on illumination series data and machine learning. Illumination series are acquired using a device which allows for generating of arbitrary illumination environments by projecting illumination patterns onto a …
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Classifications

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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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    • 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
    • G06K9/4604—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
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    • G06K9/6256—Obtaining sets of training patterns; Bootstrap methods, e.g. bagging, boosting
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    • G06K9/6279—Classification techniques relating to the number of classes
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    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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    • G06—COMPUTING; CALCULATING; COUNTING
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    • G—PHYSICS
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    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
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    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/55—Specular reflectivity
    • G01N21/57—Measuring gloss
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    • G06K2209/19—Recognition of objects for industrial automation

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