From the commercial and the technical development standpoints, engineering drawings in electrical computer-aided-design format are more advantageous than those in the traditional paper-based format. With the large stocks of paper drawings in factories and institutes, the demand for conversion is urgent and strong. Currently, several commercial systems are available to convert paper drawings to CAD. However, due to the high complexity and some unpredictable deformation during the processing of drawings, there still exist some problems. Several key solutions to these problems, which are employed in a practical automatic CAD conversion system AVSED, are discussed in this paper. These include the extraction of characters from drawings using a novel text/graphics separation algorithm, complex nonlinear exponential AR (CNEAR) model based character recognition, rapid thinning algorithm and its implementation of hardware, adaptive node regulation algorithm and cross-node tracing algorithm to obtain accurate vectorization of cross lines and neural network based arrow recognition. With these techniques high speed and accurate rate of processing can be achieved in AVSED. The general architecture and algorithms of AVSED are also described. Finally, the AVSED processing results of an original raster drawing is given, and a conclusion is drawn based on the comparison of results by AVSED and a commercial system VPmaxNT.
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