Texture Detection of Aluminum Foil Based on Top-Hat Transformation and Connected Region Segmentation

Joint Authors

He, Fei
Hu, Yuxing
Wang, Jian

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