Industrial complex scene small target defect detection system based on attention mechanism

Abstract

This invention discloses an attention-based system for detecting small-target defects in complex industrial scenes, belonging to the field of industrial vision inspection technology. It includes modules for image acquisition, preprocessing, feature perception, candidate recognition, decision feedback, and localization optimization. The image acquisition module acquires a set of original scene images of the workpiece; the preprocessing module eliminates uneven illumination to generate standard illumination image data; the feature perception module calculates a global context association matrix through a multi-level feature perception network; the candidate recognition module parses the matrix to identify candidate defect regions and extracts local texture gradient information to construct a defect probability distribution heatmap; the decision feedback module compares the results with a sample library, outputs the decision results, and feeds back to the network to update weights; and the localization optimization module recalculates the association matrix to generate optimized defect location coordinates. This invention can improve the detection and localization accuracy of small-target defects in complex industrial scenes, adapting to the actual inspection needs of industrial sites.

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