Infrastructure Crack Segmentation: Boundary Guidance Method and Benchmark Dataset

• URL: http://arxiv.org/abs/2306.09196v1
• Date: Thu, 15 Jun 2023 15:25:53 GMT
• Title: Infrastructure Crack Segmentation: Boundary Guidance Method and Benchmark Dataset
• Authors: Zhili He, Wang Chen, Jian Zhang, Yu-Hsing Wang
• Abstract summary: This paper examines the inherent characteristics of cracks so as to introduce boundary features into crack identification. It builds a boundary guidance crack segmentation model (BGCrack) with targeted structures and modules, including a high frequency module. This paper provides a steel crack dataset that establishes a unified and fair benchmark for the identification of steel cracks.
• Score: 11.282003429161163
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Cracks provide an essential indicator of infrastructure performance degradation, and achieving high-precision pixel-level crack segmentation is an issue of concern. Unlike the common research paradigms that adopt novel artificial intelligence (AI) methods directly, this paper examines the inherent characteristics of cracks so as to introduce boundary features into crack identification and then builds a boundary guidance crack segmentation model (BGCrack) with targeted structures and modules, including a high frequency module, global information modeling module, joint optimization module, etc. Extensive experimental results verify the feasibility of the proposed designs and the effectiveness of the edge information in improving segmentation results. In addition, considering that notable open-source datasets mainly consist of asphalt pavement cracks because of ease of access, there is no standard and widely recognized dataset yet for steel structures, one of the primary structural forms in civil infrastructure. This paper provides a steel crack dataset that establishes a unified and fair benchmark for the identification of steel cracks.

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