High-Speed Railway Fastener Detection Based on a Line Local Binary Pattern

Traditional image features are not able to effectively represent railway fasteners under varied illumination and conditions. We propose the line local binary pattern encoding method that considers the relationship between the center point and its upper and lower neighborhoods. The method can effectively represent the key components of fasteners. In comparison with several state-of-the-art methods, the proposed method has good performance on detecting the completely missing and partly missing fasteners on real data sets, especially when the illumination and background are not ideal.