The invention discloses a self-adaptive
relay platen row and column coordinate detection method, and belongs to the field of
computer vision and industrial automatic detection. The method comprises the following steps: firstly, acquiring an initial detection frame of a pressing plate block by using a
deep learning model, and executing asymmetric center point compensation according to categories to determine a feature center point; then dynamically deriving a scale adaptive threshold based on a global minimum neighborhood distance, and constructing a global convex
hull and an edge
point cloud to establish a physical contour reference; then, a multi-criterion judgment condition recursive
fitting algorithm is adopted to extract a row-column biaxial frame from the fragmented
point set, and row and column attributes are automatically decoupled and judged through maximum included angle search and slope analysis; and finally, projecting the feature points to a biaxial intersection point, realizing accurate mapping from space coordinates to logic numbers, and outputting a row-column logic index. According to the method, the problem of difficulty in row and column identification caused by a complex shooting
view angle, perspective deformation and pressing plate installation deviation is effectively solved, and the accuracy and robustness of state identification of the
relay voltage plate for
electric power inspection are remarkably improved.