Study On Classification And Recognition System Of Furniture Plate Based On Machine Vision

In the process of production,furniture panels are classified,identified,and placed in a traditional manual way,which is time consuming and difficult to achieve.This article combines the actual project situation,carries on the thorough discussion to the difference between the different types of furniture plate,has designed a board classification system based on machine vision.Furniture plates are mainly composed of different colors and patterns of different textures.Therefore,the color and texture features of the plate are the main research objects.The surface color and texture information of the board is an important characteristic parameter of the surface,which not only can directly reflect the surface characteristics,but also indirectly affect the person's psychological feelings,and is directly related to the processing level,quality,price and economics of the company.However,the furniture plate has a fine and complex texture structure,and it is difficult to describe it with an exact mathematical formula.It has always been a difficult problem in the academic world.Therefore,the development of an automatic control system capable of classifying,identifying and automatically classifying furniture sheet production processes with surface textures and colors has dual theoretical and practical values.This article discusses the development history of machine vision and computer vision and its application in various industries,thus establishing a research method for furniture panel classification based on machine vision and pattern recognition.This article discusses the development history of machine vision and computer vision and its application in various industries,thus establishing a research method for furniture panel classification based on machine vision and pattern recognition.Starting from the functional requirements of sheet sorting and the structural design of the production line,a set of hardware equipment based on computers,light sources,lenses,industrial cameras,motion control cards,and mechanical execution components(robots)was constructed,and the same equipment was compared.The difference between the different models,in the premise of meeting the needs of the project,from the perspective of economic practicality of each hardware device category selection.In addition,the design ideas of the detection software are also introduced in detail so that the software has the necessary inspection and data review functions.In the aspect of image algorithm,the traditional texture classification algorithm is difficult to distinguish the same texture and different color samples in the classification of furniture plates,as well as the case of misclassification of a sample with the same texture and the same color with pattern interference.A Classification Algorithm Based on Integrated Gaussian Support Vector Machines.The method extracts texture feature parameters from the HSV color space of the color image,uses the output probability calculated by the Gaussian mixture model as the input parameter of the support vector machine,and uses the binary error correction code to extend the two classifications to multiple categories.In terms of communication,the network interface between computer and robot in the panel sorting system was discussed in detail.The basic principle of Socket and the communication framework based on TCP protocol were briefly described.According to the communication principle,the program is written so that the computer can control the robot's grasping action so as to classify and classify the plates.In the end,this paper describes the process of selecting the parameters of the feature set of the classification system and the parameters of the algorithm through experiments,and proves the effectiveness of the integrated Gaussian Support Vector Machine(SVM)classification algorithm in plate classification and identification applications.