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Proceedings Paper

Research on the multi-criteria combination in automatic recognition of marking points
Author(s): Yan An; Keyan Dong
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Paper Abstract

Objective: In the field of computer vision, the technology for the automatic recognition of coded pattern plays an important basic role in the camera calibration process of intrinsic and extrinsic parameters, the binocular image matching process and the three-dimensional reconstruction process. Therefore, in the measurement processing, the successive rate for the automatic recognition of coded pattern must be guaranteed. Method: According to analyzing the geometric information of the coded pattern (the mixed type) and basing on the existing recognition method, a new automatic recognition method is proposed, which is the effective method to solve the multi-points recognition in single image by taking the multi-feature information of the coded pattern as the recognition criteria. Result: Both the new recognition method and the old recognition method are used in identifying the one hundred coded pattern which have been actually collected. The experimental result shows that, not only the new recognition method can achieve accurate identification of coded pattern with the recognition accuracy rate of 100%, but also its processing speed is 2.38 times faster than that in the old recognition method. Conclusion: It is obvious that there are many advantages in the new automatic recognition method, including the high effective recognition, the faster executive speed and independent on the auxiliary decoding process information. The new recognition method of multi-criteria combination can provide a strong guarantee for the realization of every aspect in the work of photogrammetry.

Paper Details

Date Published: 24 November 2014
PDF: 12 pages
Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010X (24 November 2014); doi: 10.1117/12.2070685
Show Author Affiliations
Yan An, Changchun Univ. of Science and Technology (China)
Keyan Dong, Changchun Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 9301:
International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition
Gaurav Sharma; Fugen Zhou; Jennifer Liu, Editor(s)

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