EdgeFormer: edge-assisted transformer for thermal images semantic segmentation

Futian Wang; Zhongfeng Ding; Tao Shi; Jin Tang

doi:10.1117/12.2674788

2 May 2023 EdgeFormer: edge-assisted transformer for thermal images semantic segmentation

Futian Wang, Zhongfeng Ding, Tao Shi, Jin Tang

Proceedings Volume 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023); 126422G (2023) https://doi.org/10.1117/12.2674788
Event: Second International Conference on Electronic Information Engineering, Big Data and Computer Technology (EIBDCT 2023), 2023, Xishuangbanna, China

Abstract

Most problems in the power system are related to the temperature of electrical equipment. The abnormal high temperature of electrical equipment will not only cause damage to equipment itself, but also threaten the safety of people’s life and property. Therefore, patrol inspectors of power system will carry out routine inspection on electric equipment to ensure safety. Semantic segmentation for electrical equipment carries a big weight in the inspection. With the result of semantic segmentation of power equipment, patrol inspectors can quickly judge whether the temperature of power equipment is normal, and then take the corresponding action. For this reason, we propose the EdgeFormer, which is a typical end-to-end network using thermal image to segment electrical equipment. In our method, we employ an edge information extraction network to attain rich edge features to promote the segmentation performance in electrical equipment’s edges and interiors, and we also design the global enhancing module (GEM) to get rich semantic information. Besides, we also propose a feature inserting module (FIM) to fuse the feature maps from different stages together. Lots of experiments have been conducted on the LS-ETS dataset and the results show that our EdgeFormer has achieved the best performance.

Citation Download Citation

Futian Wang, Zhongfeng Ding, Tao Shi, and Jin Tang "EdgeFormer: edge-assisted transformer for thermal images semantic segmentation", Proc. SPIE 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023), 126422G (2 May 2023); https://doi.org/10.1117/12.2674788

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KEYWORDS

Semantics

Image segmentation

Thermography

Transformers

Ablation

Network architectures

Convolution

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