Research of online automatism identification algorithm based on image character sequence look-up table

Yueping Han; Yan Han; Ruihong Li

doi:10.1117/12.767387

26 February 2008 Research of online automatism identification algorithm based on image character sequence look-up table

Yueping Han, Yan Han, Ruihong Li

Proceedings Volume 6813, Image Processing: Machine Vision Applications; 681313 (2008) https://doi.org/10.1117/12.767387
Event: Electronic Imaging, 2008, San Jose, California, United States

Abstract

This paper proposes an effective approach for online inspecting and recognizing the assembly structure inside three-dimensional objects using multiple views technique and X-ray digital radiography system. During the offline study process, the paper obtains a gray image sequence of a standard sample in multiple circumferential orientations. Utilizing the idea of classifying identification, the paper locates and extracts different characters of different parts in each image of the sequence and establishes corresponding character sequence libraries. In online detection stage, the program finds the optimum solutions to all different target parts in the library with bisearch method and carries out exactness image matching with correlation coefficient weighted of multi-character via Bayes decision. Aiming at the issue of some objects may be occluded by others in a scene, the paper puts forward to rotate the product some certain angles and re-match. Furthermore, the paper analyzes the relationships of misjudgment ratio with product assembling tolerance, the size of target part and identifying velocity. Based on this approach, the first domestic X-ray automatism detection system has been developed and it is successfully applied in online detecting some axis symmetric products which assembly structures inside are complex.

Citation Download Citation

Yueping Han, Yan Han, and Ruihong Li "Research of online automatism identification algorithm based on image character sequence look-up table", Proc. SPIE 6813, Image Processing: Machine Vision Applications, 681313 (26 February 2008); https://doi.org/10.1117/12.767387

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