Abstract
This paper presents a novel unified framework for authenticating topology integrity of 2D heterogeneous engineering CAD drawings. Topology information, through which a variety of engineering reports are generated, plays the most important role in the engineering CAD field. However, topology integrity authentication for engineering CAD drawings is still in its infancy and few efforts were made in the literature. By efficiently extracting topological and geometric features regardless of their heterogeneity with respect to geometrical shape and topology representation, the proposed framework supports verifying topology integrity for various heterogeneous engineering CAD drawings, such as process flow diagrams (PFD), piping and instrument drawings (P&ID), piping isometric drawings (ISO) as well as sectional drawings. Topology authentication is achieved through embedding local topological features into geometric features by introducing a generic and effective semi-fragile watermarking scheme. A novel descriptor, called topology local binary patterns (T-LBP), is proposed to extract local topological features of heterogeneous drawings. Theoretical analysis and experiments have demonstrated the discrimination power, robustness and sensitivity of the proposed T-LBP descriptor. We also carry out further experiments to prove that the proposed framework can not only detect and locate malicious topological modifications, but also yield strong robustness against various topology preserving modifications.
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Acknowledgments
The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the quality of the paper. They are also grateful to Beijing Zhongke Fulong Computer Technology Co., Ltd for the engineering CAD drawings used in this paper. This work is supported by the National Natural Science Foundation of China (61300160).
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Su, Z., Zhou, L., Mao, Y. et al. A unified framework for authenticating topology integrity of 2D heterogeneous engineering CAD drawings. Multimed Tools Appl 76, 20663–20689 (2017). https://doi.org/10.1007/s11042-016-3994-x
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DOI: https://doi.org/10.1007/s11042-016-3994-x