This invention discloses a cable production identification and
monitoring system and method based on cable images, belonging to the field of image recognition technology. The
system includes: acquiring a sequence of cable
surface depth images to construct a
grayscale surface map along the cable
surface depth direction; using the central
ridge of the
grayscale surface map as a dynamic
axis of symmetry, detecting candidate pixels through multi-scale morphological top-hat transformation to form a symmetrical residual distribution map; combining the eight-neighbor
gradient direction field and Hessian matrix curvature to remove false defect points, obtaining an effective image, and inputting it into a pre-trained multi-task neural network to simultaneously output a defect segmentation
mask and category
label; generating a three-dimensional
mesh model with dimensional accuracy through Poisson
surface reconstruction; and finally, using the physical coordinates of the defect center to drive a
laser marking
machine to mark a QR code containing key information, which is then associated and stored in a
blockchain database. This application improves the accuracy and efficiency of defect identification, realizing the quantitative characterization and full lifecycle management of defects.