激光与光电子学进展, 2019, 56 (10): 101004, 网络出版: 2019-07-04
基于生成式对抗网络的细小桥梁裂缝分割方法 下载: 1695次
Method for Small-Bridge-Crack Segmentation Based on Generative Adversarial Network
图像处理 桥梁路面裂缝 深度学习 超分辨率图像 生成式对抗网络 语义分割 image processing bridge pavement crack deep learning super-resolution image generative confrontation network semantic segmentation
摘要
提出了一种基于生成式对抗网络的细小桥梁裂缝分割方法。该方法在判别器结构中引入分割分支,将生成式对抗网络与语义分割网络合二为一,兼具超分辨率图像重建功能与分割功能。在处理细小桥梁裂缝分割问题时,该方法先将低分辨率的细小桥梁裂缝图像转换为超分辨率的粗大型桥梁裂缝图像,再对转换后的超分辨率图像进行分割。实验结果表明,该方法更容易识别出细小桥梁裂缝并实现准确分割,与传统的分割方法相比,该方法的分割召回率提高了6%,平均交并比提高了10%。
Abstract
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.
李良福, 胡敏. 基于生成式对抗网络的细小桥梁裂缝分割方法[J]. 激光与光电子学进展, 2019, 56(10): 101004. Liangfu Li, Min Hu. Method for Small-Bridge-Crack Segmentation Based on Generative Adversarial Network[J]. Laser & Optoelectronics Progress, 2019, 56(10): 101004.