Parking-lines detection based on an improved Hough transform

Jiang, Shuyu; Lu, Yinghua; Chen, Yuan; Zou, Xionggao

doi:10.1117/12.2300492

Cited by 1 publication

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“…e yellow rectangular region is used to frame and divide the clustering region of each obstacle point (see Figure 5). e clustering regions taken by yellow rectangles in Figure 5 are denoted as O, and the remaining area is the nonobstacle area, denoted as F. [31], the most mature straight line detection method, is used to detect the parking line in the nonobstacle area F. e basic idea of the Hough transform is to measure space point (x i , y i ) into a parameter space curve. e points with the same parameter characteristics intersect in the parameter space after transformation, and the characteristic curve is detected by judging the degree of accumulation at the intersection points.…”

Section: Sse � 􏽘mentioning

confidence: 99%

Parking Space Detection and Path Planning Based on VIDAR

Gao

Jiang

et al. 2021

Journal of Robotics

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The existing automatic parking algorithms often neglect the unknown obstacles in the parking environment, which causes a hidden danger to the safety of the automatic parking system. Therefore, this paper proposes parking space detection and path planning based on the VIDAR method (vision-IMU-based detection and range method) to solve the problem. In the parking space detection stage, the generalized obstacles are detected based on VIDAR to determine the obstacle areas, and then parking lines are detected by the Hough transform to determine the empty parking space. Compared with the parking detection method based on YOLO v5, the experimental results demonstrate that the proposed method has higher accuracy in complex parking environments with unknown obstacles. In the path planning stage, the path optimization algorithm of the A ∗ algorithm combined with the Bezier curve is used to generate smooth curves, and the environmental information is updated in real time based on VIDAR. The simulation results show that the method can make the vehicle efficiently avoid the obstacles and generate a smooth path in a dynamic parking environment, which can well meet the safety and stationarity of the parking requirements.

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Section: Sse � 􏽘mentioning

confidence: 99%