Research And Implementation On Automation Detection Technology Of Foreign Fiber In Cotton Flow Based On Machine Vision

Cotton is an important raw material, many industries are required to use cotton products. And the foreign fibers in cotton is very sidespread, foreign fibers will cause the quality of the cotton products declined, not only brought huge economic losses to farmers and cotton textile industry, but also affect the reputation of cotton products in the international market. In recent years, based on machine vision and automatic detection system has been widely applied in various fields because of its highly accuracy, highly reliability, highly efficiency and easy memory expansion and other characteristics, This system can greatly improving production efficiency and production automation. Through in-depth analysis and comparative study of other foreign fiber detection method, an automation foreign fiber dection method based on machine vision is proposed, the main contents are as follows:1) Based on the analysis of the advantages and disadvantages of the existing system, fully taking into account the acquisition rate, image resolution, the width of the field view, focal length and other conditions, finally select the desired hardware devices of the automation foreign fiber dection system; according to different characteristics of different types of foreign fibers, designed a combination light source system with sun light source and UV light source. After the acquisition tests using the selected hardware, the image detail is sharp, clear.2) Based on the research of mathematical morphology and edge detection theory, a lot of experiment proved that the classicial edge detector operator can not meet the application requirements of this article. After a full analysis of a lot of different fiber morphology image, a foreign fiber detection algorithm with three processes include improved morphology edge detection operator, sub-pixel edge detection based on Zernike Moments and three neighborhood non-maxima suppression algorithm is proposed, simulation results show that the detection effect of foreign fiber is good and the time required for detection is less than other method.3) Based on the analysis of implementation constraints of automation foreign fiber detection system: hareware requirements and time requirements, a foreign fiber remove mechanism was determined. And then the foreign fiber detection and identification algorithm software platform based on object-oriented thinking and modular thinking was designed to ensure the high-speed cameras on cotton flow both sides can work in parallel and control the remove mechanism together. Finally, detailed design and testing of the entire automation foreign fiber detection system base on machine vision was done.The experiment show that the developed system can meet the actual needs and highly stability and highly recognition rate.