Study On The Design Of Coded Target And Information Processing In Close-Range Photogrammetry

In the field of reverse engineering, digital close-range photogrammetry is emerging to be the most extensible and powerful technique for industrial on-site measurement. It is being widely used to meet the requirement of design and manufacturing of products like automobile body & inner decoration, airplane body & skeleton, large antenna, etc. However, as tasks for measuring large and complex objects become much more common today, a shortage of the amount of coded target in existing systems has affected the advantage of this technique to implement overall measurements. It needs to find the solution which could be able to both expand the amount of coded target and enhance the capabilities of data processing to ensure the accuracy and efficiency of the system.In this thesis, the design concept of the coded target together with decoding strategies is represented. An improved design of coded target scheme and its corresponding decoding algorithm are put forward. For this purpose, techniques for auto information processing such as image processing, image analysis, and pattern recognition are researched. Furthermore, a rectification solution and a correction model are provided to solve problems related with real scene experiments.Firstly, the state of arts of industrial close-range photogrammetry is introduced. Based on the analysis of the two main types of coded target schemes, a new type of scheme is invented in order to fulfill the mission. The new scheme could be considered as upgrading the concentric ring type scheme by a start sign. Reserving all merits of the original scheme, this "starter" eliminates the effect of "rotation distinction" which is one main reason that limits coded target amount.Secondly, the decoding strategy and decoding algorithm are designed, and many tests of simulated ideal images are made. All related theories and techniques such as image processing & analyzing, pattern recognition are discussed. Decoding process produces perfect results in these tests.Finally, the decoding process in real scene image experiments is developed and tested. There are two problems during the test. One is that some starter sign may stick to surrounding region which makes decode fail. A 2-step rectification solution is designed to fix it. The other problem is that the targets of far and tilted photographing position are difficult to be decoded. For this, a correction model is established to process the image by utilizing projective transform model and its data relation. Both the rectification solution and the correction model are proved to be very effective and reasonable by tests.In conclusion, the entire solution proposed by the author is proved to be effective and practical. The amount of coded target is considerably enlarged; the decoding process is accurate and efficient; the rectification solution and the correction model are effective to handle the un-ideal data of real images. Moreover, now that the correction model is oriented to situations wherever projective transformation is involved, it could be used to solve similar problems in close-range photogrammetry and image processing.