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Fatigue driving behavior recognition in all-weather real driving environments is a challenging task. Accurate recognition of fatigue driving behavior is helpful to improve traffic safety. The facial landmark detector is crucial to fatigue driving recognition. However, existing facial landmark detectors are mainly aimed at stable front face color images instead of side face gray images, which is difficult to adapt to the fatigue driving behavior recognition in real dynamic scenes. To maximize the driver's facial feature information and temporal characteristics, a fatigue driving behavior recognition method based on a multi-scale facial landmark detector (MSFLD) is proposed. First, a spatial pyramid pooling and multi-scale feature output (SPP-MSFO) detection model is built to obtain a face region image. The MSFLD is a lightweight facial landmark detector, which is composed of convolution layers, inverted bottleneck blocks, and multi-scale full connection layers to achieve accurate detection of 23 key points on the face. Second, the aspect ratios of the left eye, right eye and mouth are calculated in accordance with the coordinates of the key points to form a fatigue parameter matrix. Finally, the combination of adaptive threshold and statistical threshold is used to avoid misjudgment of fatigue driving recognition. The adaptive threshold is dynamic, which solves the problem of the difference in the aspect ratio of the eyes and mouths of different drivers. The statistical threshold is a supplement to solve the problem of driver's low eye threshold and high mouth threshold. The proposed methods are evaluated on the Hunan University Fatigue Detection (HNUFDD) dataset. The proposed MSFLD achieves a normalized mean error value of 5.4518%, and the accuracy of the fatigue driving recognition method based on MSFLD achieves 99.1329%, which outperforms that of state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Fasteners are an important part of railway security. The application of computer vision and image processing on fastener detection has become a research hot spot. However, most of the researches have focused on the missing and damage detection of fasteners up to now. In this paper, a method based on image processing is proposed to locate the center of the hexagon nut in the railway fastener. The precise position of the hexagon nut can be used for the automatic replacement of the nut, which is of great significance for the automatic railway construction and maintenance. The locating method proposed in this paper can be divided into two steps. First, the improved Canny detector which combines surrounding suppression and iterative excitation is used to extract the contours of the fastener. Then, a multifeature hierarchical locating (MHL) algorithm is proposed, which integrates the circle contour of the gasket and the hexagon features of the nut. The experimental results show that the improved Canny detector suppresses noises effectively and highlights the contours of fastener. The MHL algorithm in the next step improves the locating accuracy remarkably while guaranteeing the robustness meantime. [ABSTRACT FROM AUTHOR]

Rail corrugation dynamic measurement techniques are critical to guarantee transport security and guide rail maintenance. The chord-based method is one of the most common methods nowadays. However, for corrugation broadband measurement varied from 30 mm to 60 m, this method is faced with two severe challenges in actual applications: one is that the effective measuring range of traditional single chord models cannot cover the required broadband, and the other is that the common frequency sampling method (FSM) is unavailable to design the FIR inverse filters for asymmetrical chord and multipoints chord models. To solve the two problems, a practical combination-chord model (CCM) is proposed in this paper. For the first problem, the model is constructed on the existing three-point asymmetrical chord platform. Through the flexible combination of three sensors, CCM integrates the advantages of long-wave measurement from the two-point chord model and shortwave measurement from the three-point asymmetrical chord model, and realizes the corrugation broadband measurement in one platform successfully. For the second problem, the least square (LS) is employed to design the inverse filter. Compared with FSM, the design process is more unlimited and easier for the user. More important, even with the same output filter order, the filter performance designed by LS is better than that by FSM. The efficiency of CCM and the superiority of inverse filter designed by LS were verified by vast experiments. The results could achieve the design target. [ABSTRACT FROM PUBLISHER]