Research on tobacco foreign body detection device based on machine vision
Chao Mi, Chen Kai, Zhang Zhiwei
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.