基于电子版的建筑图纸识别是工程图纸识别领域的一个重要分支。
Electronic architectural drawing recognition technique is a main branch in engineering drawing recognition field.
工程图纸扫描识别及矢量化在国内外虽然已经进行了相当长时间的研究，但依然未达到智能理解的程度。
The research of scanning, discerning and vectorization of engineering drawing has been carried out for quite a long-time, but it has not reached the degree of intelligence and understand.
基于径向基概率神经网络，提出一种扫描工程图纸图像分割后的图形符号识别方法。
A novel graphic symbol recognition approach of engineering drawings based on radial basis probabilistic neural networks (RBPNN) is proposed.
提出一种统计识别与结构识别相结合的符号识别方法，以识别工程图纸中的各种符号，并达到了很好的识别效果。
A statistic and structure integrated approach for recognizing all kinds of symbols on engineering drawing is presented. It achieves a good recognition result.
圆弧识别是工程图纸矢量化研究中的重点和难点。
Recognition for arcs is an important and difficult problem in the study on vectorization of scanned image of engineering drawings.
工程图纸扫描识别一直是模式识别中的难点问题。
The recognition of scanned image of engineering drawing is very difficult in pattern recognition.
并构造了特征识别系统，对工程图纸进行识别处理，作为知识库的辅助系统。
Also this paper constructs feature recognition systems which can recognize and deal with engineering graphs and can be regarded as the auxiliary system of repository.
工程图纸中电气符号的自动识别是实现电气工程图纸矢量化的基础。
The automatic recognition of electro-symbol is the base of engineering drawing vectorization.
摘要：工程图纸扫描输入与识别理解是CAD推广和普及的关键步骤之一，主要解决已有大量图纸再利用问题。
Abstract: The scanning input and recognition of engineering drawings is a key step in CAD, and is to reuse lots of engineering drawings.
在工程图纸扫描图象识别研究中，圆弧识别是识别算法中的重点和难点。
In study on recognition of scanned image of engineering drawings, the recognition for circular arcs is an important and difficult problem.
在工程图纸扫描图象识别研究中，圆弧识别是识别算法中的重点和难点。
In study on recognition of scanned image of engineering drawings, the recognition for circular arcs is an important and difficult problem.
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