Dataset Information

Visual-Based Defect Detection and Classification Approaches for Industrial Applications-A SURVEY.

ABSTRACT: This paper reviews automated visual-based defect detection approaches applicable to various materials, such as metals, ceramics and textiles. In the first part of the paper, we present a general taxonomy of the different defects that fall in two classes: visible (e.g., scratches, shape error, etc.) and palpable (e.g., crack, bump, etc.) defects. Then, we describe artificial visual processing techniques that are aimed at understanding of the captured scenery in a mathematical/logical way. We continue with a survey of textural defect detection based on statistical, structural and other approaches. Finally, we report the state of the art for approaching the detection and classification of defects through supervised and non-supervised classifiers and deep learning.

SUBMITTER: Czimmermann T

PROVIDER: S-EPMC7085592 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Visual-Based Defect Detection and Classification Approaches for Industrial Applications-A SURVEY.

Czimmermann Tamás T Ciuti Gastone G Milazzo Mario M Chiurazzi Marcello M Roccella Stefano S Oddo Calogero Maria CM Dario Paolo P

Sensors (Basel, Switzerland) 20200306 5

This paper reviews automated visual-based defect detection approaches applicable to various materials, such as metals, ceramics and textiles. In the first part of the paper, we present a general taxonomy of the different defects that fall in two classes: visible (e.g., scratches, shape error, etc.) and palpable (e.g., crack, bump, etc.) defects. Then, we describe artificial visual processing techniques that are aimed at understanding of the captured scenery in a mathematical/logical way. We cont ...[more]

PMID: 32155900

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Project description:BACKGROUND: Several classification schemes, each with its own philosophy and categorizing method, subgroup low back pain (LBP) patients with the intent to guide treatment. Physiotherapy derived schemes usually have a movement impairment focus, but the extent to which other biological, psychological, and social factors of pain are encompassed requires exploration. Furthermore, within the prevailing 'biological' domain, the overlap of subgrouping strategies within the orthopaedic examination remains unexplored. The aim of this study was "to review and clarify through developer/expert survey, the theoretical basis and content of physical movement classification schemes, determine their relative reliability and similarities/differences, and to consider the extent of incorporation of the bio-psycho-social framework within the schemes". METHODS: A database search for relevant articles related to LBP and subgrouping or classification was conducted. Five dominant movement-based schemes were identified: Mechanical Diagnosis and Treatment (MDT), Treatment Based Classification (TBC), Pathoanatomic Based Classification (PBC), Movement System Impairment Classification (MSI), and O'Sullivan Classification System (OCS) schemes. Data were extracted and a survey sent to the classification scheme developers/experts to clarify operational criteria, reliability, decision-making, and converging/diverging elements between schemes. Survey results were integrated into the review and approval obtained for accuracy. RESULTS: Considerable diversity exists between schemes in how movement informs subgrouping and in the consideration of broader neurosensory, cognitive, emotional, and behavioural dimensions of LBP. Despite differences in assessment philosophy, a common element lies in their objective to identify a movement pattern related to a pain reduction strategy. Two dominant movement paradigms emerge: (i) loading strategies (MDT, TBC, PBC) aimed at eliciting a phenomenon of centralisation of symptoms; and (ii) modified movement strategies (MSI, OCS) targeted towards documenting the movement impairments associated with the pain state. CONCLUSIONS: Schemes vary on: the extent to which loading strategies are pursued; the assessment of movement dysfunction; and advocated treatment approaches. A biomechanical assessment predominates in the majority of schemes (MDT, PBC, MSI), certain psychosocial aspects (fear-avoidance) are considered in the TBC scheme, certain neurophysiologic (central versus peripherally mediated pain states) and psychosocial (cognitive and behavioural) aspects are considered in the OCS scheme.

Dataset Information

Visual-Based Defect Detection and Classification Approaches for Industrial Applications-A SURVEY.

Publications

Visual-Based Defect Detection and Classification Approaches for Industrial Applications-A SURVEY.

Similar Datasets

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