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Indexed by:会议论文

Date of Publication:2018-01-01

Included Journals:CPCI-S

Volume:10602

Key Words:corrosion recognition; convolutional neural networks; sliding window technique; ship steel structures

Abstract:Ship structures are subjected to corrosion inevitably in service. Existed image-based methods are influenced by the noises in images because they recognize corrosion by extracting features. In this paper, a novel method of image-based corrosion recognition for ship steel structures is proposed. The method utilizes convolutional neural networks (CNN) and will not be affected by noises in images. A CNN used to recognize corrosion was designed through fine-turning an existing CNN architecture and trained by datasets built using lots of images. Combining the trained CNN classifier with a sliding window technique, the corrosion zone in an image can be recognized