Design of an intelligent product recognition system based on image correction

In the use of barcodes for commodity identification, the barcode recognition of non-planar commodities has the problem of a high error rate. Hence, designing commodity intelligent systems based on image correction was carried out. The proposed fisheye-image aberration correction technique was used to eliminate the aberrations in the image and improve the barcode recognition accuracy. At the same time, it was combined with the hardware system to recognize commodities rapidly. Through experiments, it is verified that the system has the function of commodity recognition and can improve the accuracy of non-planar commodity barcode recognition.