This invention relates to the field of industrial visual intelligent inspection technology, and in particular to an intelligent
visual inspection system for surface defects of
label paper. The
system continuously acquires multiple frames of images of the same
label area during roll-to-roll feeding, establishes spatial correspondence between adjacent frames, and calculates the time-series changes in
grayscale distribution, edge position, and texture features of the divided structural regions. Through continuous discrimination, progressively changing areas are identified as process evolution areas. Areas that do not meet the continuous change pattern are anomaly screened and defect identification signals are generated. This solution changes the
processing method based on single-frame matching tolerance for defect judgment, maintaining anomaly identification stability under tension fluctuations or local deformation conditions, and is suitable for detecting surface defects of various types of labels.