Open Access

ARTICLE

SAM Era: Can It Segment Any Industrial Surface Defects?

by Kechen Song^1,2,*, Wenqi Cui², Han Yu¹, Xingjie Li¹, Yunhui Yan^2,*

1 National Key Laboratory of Advanced Casting Technologies, Shenyang, 110022, China
2 School of Mechanical Engineering & Automation, Northeastern University, Shenyang, 110819, China

* Corresponding Authors: Kechen Song. Email: ; Yunhui Yan. Email:

(This article belongs to the Special Issue: Machine Vision Detection and Intelligent Recognition)

Computers, Materials & Continua 2024, 78(3), 3953-3969. https://doi.org/10.32604/cmc.2024.048451

Received 08 December 2023; Accepted 31 January 2024; Issue published 26 March 2024

Abstract

Segment Anything Model (SAM) is a cutting-edge model that has shown impressive performance in general object segmentation. The birth of the segment anything is a groundbreaking step towards creating a universal intelligent model. Due to its superior performance in general object segmentation, it quickly gained attention and interest. This makes SAM particularly attractive in industrial surface defect segmentation, especially for complex industrial scenes with limited training data. However, its segmentation ability for specific industrial scenes remains unknown. Therefore, in this work, we select three representative and complex industrial surface defect detection scenarios, namely strip steel surface defects, tile surface defects, and rail surface defects, to evaluate the segmentation performance of SAM. Our results show that although SAM has great potential in general object segmentation, it cannot achieve satisfactory performance in complex industrial scenes. Our test results are available at: https://github.com/VDT-2048/SAM-IS.

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Keywords

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