Research On Target Recognition And Location Of Manipulator Based On Computer Vision

With the rapid developments of computer technology, image processing technology and pattern recognition technology, machine vision is applied more widely. As one important way to obtain environment information, the machine vision can improve robotic flexibilities and autonomy. It is a key technology that how robots with vision to capture exact image information, as well as to extract the feature parameters of components real-timely, to recognize the component types, and to judge the position and posture of component. Based on the reason, the paper presents the algorithms of target recognition and position in industrial robot, especially real-time match recognition technology and space position technology in detail. The main task follows:1. To solve the problem of image matching under complex conditions including background and uneven illumination, a work-piece recognition algorithm based on edge matching app roach is imp roved. The algorithm enhances primitive image and temp late image by spline wavelet, adopts the edge information captured by Canny operator as a matching feature, applies improved Hausdorff distance to measure the degree of similarity between two objects and performs the search by adaptive genetic algorithm based on population generation gap information. The efficiency of the genetic algorithm is imp roved obviously without loss of quality. Experimental results show that the proposed algorithm not only speeds up the matching process greatly and is robust to the illumination variation but also effectively solves the problem of image matching and recognition when the edge information is not easy to be extracted.2. To solve the problem of work-piece image matching under the complex circumstance of translation, rotation, scale and part of occlusion, an algorithm of work-piece recognition based on SIFT (Scale Invariant Feature Transform) is suggested in this paper. The algorithm uses SIFT characteristics as matching features, then introduces the Euclidean distance as the similarity metrics of image matching, and uses a method of setting a threshold value to delete the false matching points. The experimental results proved that the algorithm can effectively solve stereo matching problems of work-piece images including translation, rotation, scale and part of occlusion.3.Wavelet transform provides itself with the capability of data compression and detecting local signal mutation, while scale invariant feature transform (SIFT) have the invariant ability of translation, rotation, scale and part of occlusion. An effective method of work-piece image matching is proposed by combining wavelet transform with SIFT. The smooth image of coarse scale can be obtained through wavelet decomposition for the original image and the model image by this method. The key points are detected using difference of Gaussians (DoG) operator and are matched using Euclidean distance, then the points of error matching are eliminated. Therefore, combination of these two methods can effectively reduce computation cost for work-piece image matching and the dependence on image acquisitive position, direction, light condition etc, which imp roves the algorithm application.4. In order to satisfy the requirements of hardware and real-time performance, the topic offers a vector matching method for part recognition based on vision using the embedded intelligent camera of DSP6000 (hereinafter referred to as VC4016) with the problem in automatic positioning, recognizing, counting and classing etc. in the process of manufacture. Extracting the feature of each part and building the corresponding relation of vector, the work piece can be recognized by making use of the matching method of characteristic number and eigenvector based on higher order neural network. After using color conversion, RIC image processing technology and Socket communication technique, to achieve software development about Automatic recognition and positioning system of work-piece.5. Three-dimensional reconstruction of target, mainly from the construction of visual system to start, has been studied. By analyzing usual camera model and its calibration method,a method was proposed about solving the pose relation between two cameras. X-corner patterns are used in camera calibration. In order to do online calibration for blurred image and improving image definition on calibration board, we proposed a method for X-corner detection based on the special character of X-corners, by using image enhancement based on wavelet analysis on calibration board. Using markers in image coordinates system, calibration parameters of two cameras and the pose relation about two cameras, image points about two cameras in left and right coordinate system can be converted into the same coordinate system, so solving of the spatial point can be simplified.