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Recognition of Multifunctional Coded Target in Single-camera Mobile 3D-vision Coordination Measurement
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作者 XU Zhi-hua XIA Ling-li YU Zhi-jing 《Semiconductor Photonics and Technology》 CAS 2009年第3期167-172,共6页
Single-camera mobile-vision coordinate measurement is one of the primary methods of 3D-coordinate vision measurement, and coded target plays an important role in this system. A multifunctional coded target and its rec... Single-camera mobile-vision coordinate measurement is one of the primary methods of 3D-coordinate vision measurement, and coded target plays an important role in this system. A multifunctional coded target and its recognition algorithm is developed, which can realize automatic match of feature points, calculation of camera initial exterior orientation and space scale factor constraint in measurement system. The uniqueness and scalability of coding are guaranteed by the rational arrangement of code bits. The recognition of coded targets is realized by cross-ratio invariance restriction, space coordinates transform of feature points based on spacial pose estimation algorithm, recognition of code bits and computation of coding values. The experiment results demonstrate the uniqueness of the coding form and the reliability of recognition. 展开更多
关键词 coded target mobile vision 3D-coordinates measurement pose estimate match of targets
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Non-iterative image feature matching algorithm based on reference point correspondences 被引量:1
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作者 张维中 张丽艳 +2 位作者 王小平 丁志安 周玲 《Journal of Southeast University(English Edition)》 EI CAS 2007年第2期190-195,共6页
Based on the coded and non-coded targets, the targets are extracted from the images according to their size, shape and intensity etc., and thus an improved method to identify the unique identity(D) of every coded ta... Based on the coded and non-coded targets, the targets are extracted from the images according to their size, shape and intensity etc., and thus an improved method to identify the unique identity(D) of every coded target is put forward and the non-coded and coded targets are classified. Moreover, the gray scale centroid algorithm is applied to obtain the subpixel location of both uncoded and coded targets. The initial matching of the uncoded target correspondences between an image pair is established according to similarity and compatibility, which are based on the ID correspondences of the coded targets. The outliers in the initial matching of the uncoded target are eliminated according to three rules to finally obtain the uncoded target correspondences. Practical examples show that the algorithm is rapid, robust and is of high precision and matching ratio. 展开更多
关键词 reference points detection coded and non-coded target SUBPIXEL gray scale centroid point correspondence
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