For important camera calibration in the field of computer vision, a new target form, namely, a grid spherical target (GST) that is different from the spherical target, is proposed. The GST has advantages of spherical and checkerboard targets because of the grid on the sphere. And the latitude and longitude circles and the intersection points between latitude and longitude circles on the GST are used to calibrate the camera. Firstly, the Image of Absolute Conic should be obtained using the elliptic curves of latitude and longitude circles on the GST in the images. After obtaining the initial intrinsic and extrinsic parameters of the camera using the Image of Absolute Conic, optimum solutions of the intrinsic and extrinsic parameters are solved through nonlinear optimization by using the latitude circles and the intersection points of the latitude and longitude lines. Finally, the effectiveness of the GST-based method is proven in simulation and physical experiments.

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Most of the existing calibration methods for binocular stereo vision sensor (BSVS) depend on a high-accuracy target with feature points that are difficult and costly to manufacture. In complex light conditions, optical filters are used for BSVS, but they affect imaging quality. Hence, the use of a high-accuracy target with certain-sized feature points for calibration is not feasible under such complex conditions. To solve these problems, a calibration method based on unknown-sized elliptical stripe images is proposed. With known intrinsic parameters, the proposed method adopts the elliptical stripes located on the parallel planes as a medium to calibrate BSVS online. In comparison with the common calibration methods, the proposed method avoids utilizing high-accuracy target with certain-sized feature points. Therefore, the proposed method is not only easy to implement but is a realistic method for the calibration of BSVS with optical filter. Changing the size of elliptical curves projected on the target solves the difficulty of applying the proposed method in different fields of view and distances. Simulative and physical experiments are conducted to validate the efficiency of the proposed method. When the field of view is approximately 400 mm × 300 mm, the proposed method can reach a calibration accuracy of 0.03 mm, which is comparable with that of Zhang’s method.

The track circuit is widely used in the railway network for safety, and the corresponding track circuit equipment is laid almost every railway station, which provides an extremely important information service for the safe driving of the train. In this paper, we proposed a two-phase detection algorithm for the state of the signal equipment of the track circuit, which is used for automatic safety detection of the status of the track circuit signal equipment in the railway signal room. Compared with the traditional inspection method of inspection workers, our proposed detection algorithm of signal state greatly improves the efficiency of security inspection, and in the experimental results, the proposed method outperforms other methods in different situations.

Most of the existing calibration methods for binocular stereo vision sensor (BSVS) depend 13 on high-accuracy target with feature points that are difficult to manufacture and costly. In complex 14 light conditions, optical filters are used for BSVS, but they affect imaging quality. Hence, the use of