VISION INSPECTION METHOD BASED ON LEARNING DATA

摘要

A learning-based vision inspection method through data balancing of the present invention includes: a pre-learning step of collecting and formulating a video image from an intrinsic sample, which is a sample of an intrinsic defective product, and a false sample, which is a sample of a false defective product, displaying the video image on a feature space, and acquiring a classification criterion which is a boundary of an intrinsic area where the intrinsic data is positioned and a false area where the false data is positioned; a failure discrimination step of inserting test data extracted and formulated as the video image from a test object into a feature space and discriminating an area in which the test data is located on the feature space with the classification criterion as a boundary so as to discriminate the test object as an intrinsic defect or a false defect; and an additional learning step in which the test data is applied to the pre-learning step so as to correct the classification criterion in the feature space, wherein the test data is corrected through a data balancing step such that the intrinsic data and the false data compose a first data group with the same number. The failure discrimination step and the additional learning step are repeatedly performed.