Detection And Recognition System Based On Machine Vision Research And Applications

Seasoning packets production machine malfunction, production line vibration and other factors lead to seasoning packets loss in the process of instant noodle packaging. At present mainly rely on manual detection and identification. For these purposes, this paper design a machine vision detection and recognition system, using the color feature recognition and mark recognition to identify the seasoning packets loss. In order to design an effective method of instant noodle seasoning packet identification, this paper studied the characteristics of the target, on-site production process, system design requirements. Design and discuss the various components of machine vision technology, focuses on image processing method and pattern recognition method.First of all, this article describes the structure of machine vision, characteristics and application in industrial inspection, the common used method of image segmentation and image recognition algorithm. According to the production process to be resolved, on the topic of the paper selection and research content are discussed.Secondly, design the overall structure of machine vision detection and recognition system. Discusses the hardware structure of machine vision system, selects each component of the machine vision and compares the performance of each part.Thirdly, describes the feature classification algorithm based on the HSI color model and recognition algorithms based on a black tag. The adaptive and performance of the algorithm has been discussed.Finally, this paper strongly emphasizes the software of system composition and function of each module. The performance of software system has been tested in laboratory and production line. The system has been successfully used in instant noodle production line. After 8 hours, 8 million packages testing shows that the system has good real-time, high accuracy, fully meets the technological requirements of production, increases the production rate of the entire production line and reduces the amount of labor workers.