VISION INSPECTION METHOD USING DATA BALANCING-BASED LEARNING, AND VISION INSPECTION APPARATUS USING DATA BALANCING-BASED LEARNING UTILIZING VISION INSPECTION METHOD

摘要

A vision inspection method using data balancing-based learning according to the present invention comprises: a prior learning step for establishing a classification criterion, which is the boundary for locations of true and false data, by collecting, mathematizing, and schematizing, in a particular space, images of true samples that are samples of genuinely defective products and false samples that are samples of falsely defective products; a defect determination step for determining the object under inspection as genuinely defective or falsely defective by introducing, into the particular space, data to be inspected, which has been extracted as an image from an object under inspection and mathematized, and determining the area in which the data to be inspected is located in the particular space with the classification criterion as the boundary; and an additional learning step for modifying the classification criterion of the particular space by applying the data to be inspected to the prior learning step, wherein the data to be inspected is modified by means of a data balancing step so that the same number of true data and false data are included, and the defect determination step and additional learning step are repeatedly carried out.