Research On Image Recognition Technology Of Mechanical Product And Its Application In Reverse Design

With the global economic integration and fierce competition in market, the enterprise must rapidly respond to the change of market and requirements of customers. In the development of mechanical products, advanced product design method is one of key factors for survival and success of enterprise. Reverse design is an advanced manufacturing model in 21st century, and has become an effective approach for improvement, innovation and rapid design for products in existence. Its relevant domain involves geometry measurement, image processing, machine vision and CAD/CAM, etc., and has important application value for research on basic principle and key technologies of reverse design.How to realize reconstruction of 3D solid objects /geometry model, mutual design and creative design for rapid prototype by acquisition and processing of image data for solid objects and geometry model is one of key problem to reverse design, and research on reverse design based on image processing has important meaning. Now, 3-D model reconstruction of mechanical product based on machine vision belongs to a hot issue. In the dissertation, based on summarization of state-of-the-art and tendency of reverse engineering and on the background of project of Sichuan province, the key technology and implementing method of integrated reverse engineering based on image processing is studied in depth, and its architecture is established. The main characteristics and creative ideas of the dissertation are as follows:(1) Based on summarization and analysis of rapid responding engineering, rapid design and their key technologies, the working theory and applied foreground of reverse design is put forward. The digitization modeling technology of integrated reverse design based on image processing is studied. A Whole Dynamic Restriction information model of mechanical product is established based on feature recognition. The reverse design system based on knowledge is built. The function of each sub-system is integrated by applying UML modeling language.(2) To facing the need of three-dimension solid digitization by computer vision, computer imaging processing methods are discussed. The problems of image match, image depth and illumination model are discussed. To deal with image noise problem, a new adaptive median filter algorithm is presented. The most important feature is that the shape of the filter window may be changed according to the mean square error of the child window. A standard testing image and an experimental result are presented. The test results show that this algorithm is superior to standard median filter in preserving the details and removing the noise.(3) A solid modeling method of reconstructing partial surface based on ICT image is put forward. It is on the basis of the integrated reverse design model of handling pictures. Moreover, after analyzing the theory of IBMR based on tracing rays and the factors of affecting the displaying efficiency, the method of improving the efficiency of IBMR for mechanical product is brought forward. The experiment system of SCU-IRE software is developed, and it is validated in application.(4) According to the need of classified recognizing mechanical products, combining fuzzy system with ANN, an improved FNN algorithm is present forward. A novel robust least square algorithm with back-propagation algorithm is put forward. And the existing knowledge of a group of mechanical parts is changed to rules with fuzzy math. In test, the algorithm in this paper has auto-recognised mechanical parts in efficiency.(5) For dealing with the flaws of David Marr's vision theory, the active vision method is researched. With the algorithm based on attention mechanism, a task-drived and "Up-Down" model is built. The Mallat wavelet multisolution method for edge detection is adopted. The model system of the saliency feature reflection is preliminarily discussed. Biology retina non-uniformly sampling and selecting to notify vision information is simulated. Range of interest (ROI) is solved by the improved sampling model. In pract...