Abstract: The evaluation process can be divided into two parts: the first part is to extract factors reflecting the quality of a line, such as slope, width, location of end points; the second part is to put these factors into an evaluator for analyzing. A BP neural network with a hidden layer was used. After training the BP network became a quality evaluator for lines and output the evaluated results on slope, width and end point's location of a line. This approach is not sensitive to scanning resolution and easy to detect poor quality lines. The method can be readily extended to verify other types of graphic elements.