The authors present a discussion of the different aspects and requirements of the CAD conversion problem and describe the general architecture and algorithms of one commercially available CAD conversion system, the GTX 5000. Scanning, vectorization, text recognition, symbol recognition, context processing, and cleanup editing subsystems of the GTX 5000 are described. Several possible alternative approaches and algorithms are also compared. EPRI (Electric Power Research Institute)-funded enhancements are discussed, including neural networks for character and symbol recognition, touching and broken character processing, and text/symbol associativity.>