Basic Research On The Key Technology Of Mechanic Part Image Tracking And Recognition

Machine vision is one of the most important parts in modern manufacture. And it involves multi-region intersection subjects including artificial intelligence, neurobiology, psychophysics, computer science, image processing, pattern recognition and so on. Machine vision achieving moving target inspection and intelligent control has become hot research in modern manufacturing field, such as automation line production and assembling monitoring, robot and manipulator guiding, product testing and classification, vision servo system, automatic understanding and recognition of part image and so on. Therefore, the tracking and recognition research of moving part image is important to modern manufacture.In this paper, on the basis of analyzing existing tracking and recognition algorithms of moving part object, new algorithms of mechanical part moving object have been studied by combining improved Genetic Algorithm, Neural Network, Wavelet transformation and the basic definitions and algorithms of Mathematic Morphology. The main researches include three aspects.Firstly, for solving the problem of nonlinear geometry distortion that three-dimensional scene is converted into two-dimensional image in image-forming system, the nonlinear distortion principal is studied and the correction algorithm based on an improved genetic algorithm optimizing neural network to implement image nonlinear geometry distortion is proposed. The experiment results show the proposed method could enhance the global searching capability of neural network, improve the convergence speed and stability and calibrate image nonlinear geometry distortion in the processing of space transformation.Secondly, tracking methods of mechanical part moving object based on motion analysis and based on image matching analysis are investigated. And inter-frame difference method, optical flow method and typical free deformation model (snake) are analyzed. The problems of centroid coordinate instability resulted from background change in inter-frame difference method, background covering and aperture in optical flow method and the convergence in snake are mainly analyzed. Tracking method of moving object based on Morphology is proposed. The experiment results show the tracking method based on the basic definition and algorithm in Mathematics Morphology provide feasible scheme for effectively detecting moving object, correctly acquiring its centroid and finishing its tracking.Finally, the recognition algorithms of mechanical moving part image are studied. In order to decrease calculation, the image segment method based on wavelet-Hilbert by adequately using the space relative information of pixels is proposed and it improves the efficiency of image segment. In the meantime, the wavelet transform method is also used to detect image edge and solve the contradiction between suppressing noise and edge location. Then, the images segmented and edge images are divided into sub-matrix images in order to get relative pixel coefficients as eigenvectors. And the relative pixel coefficients are the input sets of neural network and the recognition is carried out and it greatly reduces calculation. Because of the inherent drawbacks of sensors and the affects of environment factors, it is difficult to get the complete image information of mechanical part. It makes the feature extraction of part image and part recognition inaccurate. In order to solve this problem, the recognition algorithm based on merging reasoning rules in evidential theory is proposed. In the end, the virtual instrument of part image recognition is designed by using Labview software platform and the experiment results verify the design idea and methods of the dissertation reach expectant results.