Research And Implementation Of Digital Camera Locating Technologies In Image Processing

With the rapid development of computer technology, image identification and object locating have been stepped into the digital phase, and they have already been used in many subject areas such as cosmic discovery, industrial manufacture, communication technology, environmental protection, criminal investigation, biomedicine, cultural art, archeology, mapping and intelligent transportation. Due to this trend, this paper does research on digital camera locating. Digital camera locating has become one of the important research subjects these days, for example, vision inspection and computer vision. It has been extensively used in transportation supervision(electronic police), industrial control, military affairs and so on. Therefore, it is important to do researches on digital camera locating, and it may bring theoretical significance and application value.The paper uses the subject of 2008 Higher Education Press Cup China undergraduate mathematical contest in modeling(A-Digital camera locating) as the object of study, and does research mainly on two aspects, circular target identification and camera calibration. The main contents of research are as follows:â'ˆA detailed study is carried out on existing circular target identification methods and techniques. The advantages and disadvantages are also pointed out. The paper builds the fast circle Hough transform mathematical model, implements it in MATLAB 7.0 and uses it to locate the center of the circle in the retinal coordinate system. It is proved by the program running result that this model is better than the one which uses Sobel operator, and the coordinate of the center is more accurate.â'‰By consulting relevant literatures and analyzing various digital camera models, the paper builds target locating mathematical model with better stability and precision. This model calibrates the intrinsic and extrinsic parameters of the example. It locates the center of the circle in the retinal coordinate system on the basis of Chapter 2. The model has radial distortion model and tangential distortion model as well, which can make the calibration results more accurate.â'ŠA scientific experimental program is planned. The paper analyzes partial enlarged drawing of corner extraction, data from this model and Z.Y. Zhang's, which proves the stability and precision of this model.