Laser & Optoelectronics Progress, Volume. 56, Issue 10, 101004(2019)
Method for Small-Bridge-Crack Segmentation Based on Generative Adversarial Network
For cracks in small bridges, a segmentation method is proposed based on a generative adversarial network. This method introduces a segmental branch into the discriminator structure and combines the generative confrontation network with the semantic segmentation network. In addition, the method is capable of super-resolution image reconstruction and segmentation. To solve the problem of small-bridge-crack segmentation, this method transforms low-resolution small-bridge-crack images into super-resolution coarse-bridge-crack images, which are then segmented. The experimental results show that the proposed method facilitates the identification of small-bridge-crack and its segmentation is accurate. Compared with the traditional segmentation method, the recall rate and mean intersection over union of this method are improved by 6% and 10%, respectively.
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Liangfu Li, Min Hu. Method for Small-Bridge-Crack Segmentation Based on Generative Adversarial Network[J]. Laser & Optoelectronics Progress, 2019, 56(10): 101004
Category: Image Processing
Received: Oct. 31, 2018
Accepted: Dec. 13, 2018
Published Online: Jul. 4, 2019
The Author Email: Hu Min (longford@xjtu.edu.cn)