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In this paper, a robust recognition algorithm for encoded targets in close-range photogrammetry is proposed. Firstly, Canny detector is used to detect edges from an input image. Secondly, the least squares method is employed to fit ellipses to the set of data points yielded by the edge detector. Three restriction criteria based on length, shape, and embedding are applied to restrict the set of candidate ellipses. The initial parameters of a candidate ellipse are modified according to the information of the encoded band pattern. Finally, the identification number of the encoded target is obtained through a certification and interpretation of the arrangement of the bit segments surrounding this encoded target. The proposed algorithm has been applied to a close-range photogrammetric system, and its robustness is validated by real measuring experiments and industrial applications.

Keywords: ellipse extraction, close-range photogrammetry, encoded target, target recognition, restriction criteria

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Received May 25, 2010; revised August 9 & November 2, 2010; accepted November 28, 2010.
Communicated by Jen-Hui Chuang.
^* This work was supported by the National Natural Science Foundation of China under Grant No. 51005229, the Presidential Foundation of the Chinese Academy of Sciences under Grant No. 07AR210201, the Fund of the Chinese Academy of Sciences in Innovation Engineering under Grant No. 07A2080201 and the National Natural Science Foundation of China under Grant No. 60803108.