PHOTOVOLTAIC MODULE SEGMENTATION ALGORITHM BASED ON IMPROVED SEGFORMER

Cao Guanhua; Dang Jianwu; Yang Jingyu

doi:10.19912/j.0254-0096.tynxb.2023-1563

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (2) : 425-432. DOI: 10.19912/j.0254-0096.tynxb.2023-1563

PHOTOVOLTAIC MODULE SEGMENTATION ALGORITHM BASED ON IMPROVED SEGFORMER

Cao Guanhua¹, Dang Jianwu^1,2, Yang Jingyu¹

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Abstract

Addressing the issue of blurred and indistinguishable boundary features between Photovoltaic modules and complex backgrounds in photovoltaic images, an improved algorithm based on Segformer is introduced. During the encoding phase, a novel "block5" module is incorporated to extract higher-level semantic information. In the decoding phase, an LPCB （Learning to Predict Crisp Boundaries） module is introduced to identify more precise boundary features, resulting in highly accurate segmentation. Experimental results demonstrate that the improved photovoltaic module segmentation algorithm outperforms classical mainstream segmentation methods on a dataset of photovoltaic module images, effectively segmenting the photovoltaic module regions .

Key words

photovoltaic modules / Segformer / encode / decode / boundary feature

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Cao Guanhua, Dang Jianwu, Yang Jingyu. PHOTOVOLTAIC MODULE SEGMENTATION ALGORITHM BASED ON IMPROVED SEGFORMER[J]. Acta Energiae Solaris Sinica. 2025, 46(2): 425-432 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1563

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