The invention relates to a vision-based crossing container
truck deadbolt state detection method, and belongs to the technical field of
image processing. The crossing container
truck deadbolt state detection method based on vision comprises the steps that an image of a lock hole area is obtained through a long-focus camera on a mechanical arm, and in order to judge the opening and closing state of a lock pin, edge features of the lock hole and the lock pin need to be extracted; based on the
edge strength and in combination with
keyhole priori knowledge, carrying out deadbolt state optimization judgment; lock pin state confirmation, result output and linkage control are carried out, a detection result is directly linked with a crossing
control system to realize safety management and control of the container
truck, and if the lock pin is in a locked state, the
system forbids the container truck to pass through the crossing
handrail and keeps closed; the container truck lock pin state detection method based on
machine vision solves the problem that in an existing container truck lock pin state detection method based on
machine vision, the detection precision of
Hough transform is low under complex conditions such as uneven illumination,
noise interference, lock pin
contamination and slight deformation, and is used for improving the accuracy of container truck lock pin state detection.