Development Of The Glass Bulb Dynamic Recognition System In Two Stations Based On Machine Vision

Machine vision is a rising discipline that includes image processing, pattern recognition, artificial intelligence, artificial neural network and so on. And the detection technology of machine vision used in industry production line is a research hot spot.The main research work of this paper is as follows:1. Looking up the recent literatures and materials, knowing the application in industry field and the development about detection technology of machine vision domestically and abroad.2. For the purpose of accomplishing the requirement presented by company about glass bulb recognition, classification, count and the data management, this paper develops a glass bulb recognition system of two detection station based on machine vision and realizes the object recognition and data management. This paper settles problem of image capture collision about two detection station by the multi-thread technology in windows OS. And in order to conquer the industry field interference, this paper presents a new image segmentation algorithm. This paper designs fault diagnosis module on principle of system stability, which makes the system maintenance convenient and efficient.3. This paper realizes three function modules of software system by means of MFC in the visual C++ environment and integrates these modules. The source code is 800k totally.4. Through checking the system about stability and accuracy, the system well runs in the industry field and accomplishes the expected aim.This paper structure is combined as follows: in the first chapter, this paper introduces the development and application of machine vision domestically and abroad. In the second chapter, this paper introduces all the function modules of this system. In the third chapter, this paper studies the object recognition technology on-line of machine vision, and presents a new image segmentation algorithm. In the fourth chapter, this paper designs the software and hardware system and assures the stability. In the fifth chapter, this paper studies the method to assuring the stability of system and realizes the fault diagnosis function. In the sixth chapter, this paper introduces the data transmission and sharing in the local network. In the seventh chapter, this paper gets the system accuracy and analyzes the factors leading to system deviation. In the end, this paper presents the next work about this system in the further.