Shuzhen Tong , Qing Wang , Xuan Wei , Cheng Lu , Xiaobo Lu
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引用次数: 0
Abstract
Accurate detection of rail surface cracks is essential but also tricky because of the noise, low contrast, and density inhomogeneity. In this paper, to deal with the complex situations in rail surface crack detection, we propose modulated deformable convolution based on a graph convolution network named MDCGCN. The MDCGCN is a novel convolution that calculates the offsets and modulation scalars of the modulated deformable convolution by conducting the graph convolution network on a feature map. The MDCGCN improves the performance of different networks in rail surface crack detection, harming the inference speed slightly. Finally, we demonstrate our methods’ numerical accuracy, computational efficiency, and effectiveness on the public segmentation dataset RSDD and our self-built detection dataset SEU-RSCD and explore an appropriate network structure in the baseline network UNet with the MDCGCN.
期刊介绍：
Signal Processing: Image Communication is an international journal for the development of the theory and practice of image communication. Its primary objectives are the following:
To present a forum for the advancement of theory and practice of image communication.
To stimulate cross-fertilization between areas similar in nature which have traditionally been separated, for example, various aspects of visual communications and information systems.
To contribute to a rapid information exchange between the industrial and academic environments.
The editorial policy and the technical content of the journal are the responsibility of the Editor-in-Chief, the Area Editors and the Advisory Editors. The Journal is self-supporting from subscription income and contains a minimum amount of advertisements. Advertisements are subject to the prior approval of the Editor-in-Chief. The journal welcomes contributions from every country in the world.
Signal Processing: Image Communication publishes articles relating to aspects of the design, implementation and use of image communication systems. The journal features original research work, tutorial and review articles, and accounts of practical developments.
Subjects of interest include image/video coding, 3D video representations and compression, 3D graphics and animation compression, HDTV and 3DTV systems, video adaptation, video over IP, peer-to-peer video networking, interactive visual communication, multi-user video conferencing, wireless video broadcasting and communication, visual surveillance, 2D and 3D image/video quality measures, pre/post processing, video restoration and super-resolution, multi-camera video analysis, motion analysis, content-based image/video indexing and retrieval, face and gesture processing, video synthesis, 2D and 3D image/video acquisition and display technologies, architectures for image/video processing and communication.
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