Recognition conversion of circular graphic object for engineering drawings: the state of the art and challenges

Bin Cheng; GuangMing Lei; YaHong Wang

doi:10.1117/12.866609

19 August 2010 Recognition conversion of circular graphic object for engineering drawings: the state of the art and challenges

Bin Cheng, GuangMing Lei, YaHong Wang

Author Affiliations +

Proceedings Volume 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering; 78201C (2010) https://doi.org/10.1117/12.866609
Event: International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 2010, Xi'an, China

Abstract

This strong interest to vectorization and recognition for engineering drawings is driven by a wide spectrum of promising applications in many areas such as 3D reconstruction, information interchange, content-based retrieval to engineering drawings, 2D understanding for engineering drawings and so on. This paper reviews development level and recognition methods of vectorization and recognition of circular-typed graphics object for engineering drawings, and provides a comprehensive survey of research history and the state of the art in recognition conversion of circular-typed graphics object for engineering drawings. The approach of conversion circular-typed graphics object are divided into fitting-based methods, vector-based methods, global-based methods and integrated-based methods. The advantage and disadvantage of all existing model of circular graphics object are analyzed and compared. Research difficulties and development tendency in future are clearly discussed for engineering drawings. At the end of this survey, some detailed discussions on research challenges and future directions of vectorization and recognition for engineering drawings are also provided.

Citation Download Citation

Bin Cheng, GuangMing Lei, and YaHong Wang "Recognition conversion of circular graphic object for engineering drawings: the state of the art and challenges", Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 78201C (19 August 2010); https://doi.org/10.1117/12.866609

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