Abstract: The present disclosure provides a vehicle positioning device for vehicle vision calibration, a positioning adjustment method, and a positioning adjustment system. The vehicle positioning device includes a base, a chassis, a translation mechanism and a rotation mechanism. A to-be-calibrated vehicle is placed onto the chassis, and the chassis is provided with a stopper. The translation mechanism is arranged between the chassis and the base, and configured to drive the chassis to move in an X-axis direction in a three-dimensional coordinate system relative to the base in accordance with a translation control instruction. The rotation mechanism is arranged between the chassis and the base, and configured to drive the chassis to rotate about a Z-axis in the three-dimensional coordinate system relative to the base in accordance with a rotation control instruction.

Abstract: The present disclosure provides a vehicle positioning device for vehicle vision calibration, a positioning adjustment method, and a positioning adjustment system. The vehicle positioning device includes a base, a chassis, a translation mechanism and a rotation mechanism. A to-be-calibrated vehicle is placed onto the chassis, and the chassis is provided with a stopper. The translation mechanism is arranged between the chassis and the base, and configured to drive the chassis to move in an X-axis direction in a three-dimensional coordinate system relative to the base in accordance with a translation control instruction. The rotation mechanism is arranged between the chassis and the base, and configured to drive the chassis to rotate about a Z-axis in the three-dimensional coordinate system relative to the base in accordance with a rotation control instruction.

Abstract: The present disclosure provides a method and a device for detecting a height-limiting rod, and an automatic driving system, for use in a binocular stereo camera. The method includes: filtering out invalid points in a disparity map corresponding to a target image in accordance with a predetermined detection range, so as to acquire a valid point disparity map; projecting the valid point disparity map along an X-axis direction in a three-dimensional coordinate system onto a plane where a Y axis and a Z axis are located, and counting the quantity of valid points for each row of pixels with respect to each disparity value, so as to acquire a projection image; filtering out invalid projection points and invalid blobs in the projection image, so as to acquire a valid blob image; and back-projecting the valid blob image to the three-dimensional coordinate system, and determining a rectangular region where the height-limiting rod is located in accordance with X-axis, Y-axis and Z-axis coordinate values.

Abstract: An image edge extraction device for an automated driving system is capable of extracting an image edge in a rapid manner. The device employs an image edge extraction method that includes: acquiring a grayscale image of a target image; calculating an edge magnitude and an edge angle of the grayscale image, so as to generate an edge magnitude image and an edge angle image; detecting an edge peak of the edge magnitude image in accordance with the edge angle image, so as to acquire each edge point of the edge magnitude image and acquire an edge peak detection result; and performing double-thresholding segmentation on the edge peak detection result through a flooding method, so as to acquire an image edge of the target image.

Abstract: A method for building a camera imaging model includes: converting world coordinate values of a random point P into camera coordinate values of a target camera in accordance with a predetermined mode; converting the camera coordinate values into image coordinate values of the target camera; and converting the image coordinate values into digital image coordinate values and building the camera imaging model. The converting the image coordinate values into the digital image coordinate values includes performing a spatial sampling operation on the random point P, and adjusting coordinate values of an origin to image coordinate values through calculation. The method can be used in an automated driving system for a vehicle.

Abstract: The present disclosure provides a method and a device for detecting a height-limiting rod, and an automatic driving system, for use in a binocular stereo camera. The method includes: filtering out invalid points in a disparity map corresponding to a target image in accordance with a predetermined detection range, so as to acquire a valid point disparity map; projecting the valid point disparity map along an X-axis direction in a three-dimensional coordinate system onto a plane where a Y axis and a Z axis are located, and counting the quantity of valid points for each row of pixels with respect to each disparity value, so as to acquire a projection image; filtering out invalid projection points and invalid blobs in the projection image, so as to acquire a valid blob image; and back-projecting the valid blob image to the three-dimensional coordinate system, and determining a rectangular region where the height-limiting rod is located in accordance with X-axis, Y-axis and Z-axis coordinate values.

Abstract: The present disclosure provides a method and a device for building a camera imaging model, and an automated driving system for a vehicle, so as to describe a camera imaging system through exterior and interior parameters of a camera acquired after calibration. The method includes: converting world coordinate values of a random point P into camera coordinate values of a target camera in accordance with a predetermined mode; converting the camera coordinate values into image coordinate values of the target camera; and converting the image coordinate values into digital image coordinate values and building the camera imaging model. The converting the image coordinate values into the digital image coordinate values includes performing a spatial sampling operation on the random point P, and adjusting coordinate values of an origin to image coordinate values through calculation.

Abstract: An image edge extraction device for an automated driving system is capable of extracting an image edge in a rapid manner. The device employs an image edge extraction method that includes: acquiring a grayscale image of a target image; calculating an edge magnitude and an edge angle of the grayscale image, so as to generate an edge magnitude image and an edge angle image; detecting an edge peak of the edge magnitude image in accordance with the edge angle image, so as to acquire each edge point of the edge magnitude image and acquire an edge peak detection result; and performing double-thresholding segmentation on the edge peak detection result through a flooding method, so as to acquire an image edge of the target image.