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A Novel Knowledge-Based System for Interpreting Complex Engineering Drawings: Theory, Representation, and Implementation

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4 Author(s)
Tong Lu ; Nanjing University, Nanjing ; Chiew-Lan Tai ; Huafei Yang ; Shijie Cai

We present a novel knowledge-based system to automatically convert real-life engineering drawings to content-oriented high-level descriptions. The proposed method essentially turns the complex interpretation process into two parts: knowledge representation and knowledge-based interpretation. We propose a new hierarchical descriptor-based knowledge representation method to organize the various types of engineering objects and their complex high-level relations. The descriptors are defined using an Extended Backus Naur Form (EBNF), facilitating modification and maintenance. When interpreting a set of related engineering drawings, the knowledge-based interpretation system first constructs an EBNF-tree from the knowledge representation file, then searches for potential engineering objects guided by a depth-first order of the nodes in the EBNF-tree. Experimental results and comparisons with other interpretation systems demonstrate that our knowledge-based system is accurate and robust for high-level interpretation of complex real-life engineering projects.

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:31 ,  Issue: 8 )