Research on tobacco foreign body detection device based on machine vision

Abstract

Foreign body detection is an important aspect that affects the quality of tobacco production. This paper describes a direct foreign body detection scheme using machine vision, which uses three cameras arranged around a tobacco bale to record its multiple surfaces and directly identify foreign bodies. In this study, color sorting table method (CSTM) was first used to identify and remove color-sensitive foreign bodies; thereafter, gray threshold method and double threshold method were used to further identify and remove foreign bodies with similar colors. The experimental results indicate that the multi-step hybrid identification method proposed herein can effectively identify and remove various foreign bodies in the production process of tobacco packs, with an accuracy rate of 97.8%, which meets the industrial requirements for foreign body detection. Compared with various existing devices and methods, it has the advantages of high detection efficiency and low cost.