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Texture Detection of Aluminum Foil Based on Top-Hat Transformation and Connected Region Segmentation
Joint Authors
Source
Advances in Materials Science and Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-22
Country of Publication
Egypt
No. of Pages
7
Abstract EN
A new method of texture detection for aluminum foil based on digital image processing technology is proposed.
Top-hat transformation and image segmentation technology based on the connected domain are used to change the method of determining texture fraction by using human experience.
Compared with the brightness method, pit detection method, and EBSD technology, this method can complete quantitative detection efficiently, automatically, and accurately, and reduce the detection time and manpower.
It eliminates the instability of manual detection and ensures the accuracy of detection.
By this method, the error of test results can be controlled within 1.6%, which is much better than 7.3% of the brightness method and 4% of the pitting method.
It provides more accurate test results for the production process control of aluminum foil.
American Psychological Association (APA)
He, Fei& Hu, Yuxing& Wang, Jian. 2020. Texture Detection of Aluminum Foil Based on Top-Hat Transformation and Connected Region Segmentation. Advances in Materials Science and Engineering،Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1127948
Modern Language Association (MLA)
He, Fei…[et al.]. Texture Detection of Aluminum Foil Based on Top-Hat Transformation and Connected Region Segmentation. Advances in Materials Science and Engineering No. 2020 (2020), pp.1-7.
https://search.emarefa.net/detail/BIM-1127948
American Medical Association (AMA)
He, Fei& Hu, Yuxing& Wang, Jian. Texture Detection of Aluminum Foil Based on Top-Hat Transformation and Connected Region Segmentation. Advances in Materials Science and Engineering. 2020. Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1127948
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1127948