Digital Defect Simulation-based Data Generation for Visual Quality Inspection
Abstract
With the continuous advancement of computer vision (CV) technology, visual inspection techniques in the quality inspection industry have been rapidly developing. Data is an indispensable factor in visual detection techniques, and the demand for data is gradually increasing. Studies are progressively focusing on data generation solutions to provide high-quality data for the development of quality inspection techniques. This paper presents a morphology-based defect classification approach for visual defect simulation. Based on this classification, a digital defect simulation-based data generation solution is proposed to simulate the defects of industrial products. A new dataset SimNEU-DET is created to evaluate the proposed method, based on the open-source dataset NEU-DET. The effectiveness of the dataset is demonstrated using the object detection algorithm YOLOv5.
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- Digital Defect Simulation-based Data Generation for Visual Quality Inspection
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Published In
June 2023
293 pages
ISBN:9798400707919
DOI:10.1145/3608251
Copyright © 2023 ACM.
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Association for Computing Machinery
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Publication History
Published: 17 August 2023
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ICCMS 2023
ICCMS 2023: 2023 The 15th International Conference on Computer Modeling and Simulation
June 16 - 18, 2023
Dalian, China
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