Since chip surface symbols are used to identify chip names, performance, and functional information, their quality evaluation is an important part of chip production. Currently chip surface symbol quality evaluation methods based on machine vision are widely used, and most of them are  evaluation methods based on pixel-by-pixel comparison, facing two main problems: (1) a small amount of deformation of the symbols leads to poor quality evaluation results; (2) the internal defect characteristics of the symbols are not considered. We propose an evaluation method for structural defects of printed symbols on chip surface. Firstly, the thin-plate spline interpolation is used to align the symbols to be evaluated with the reference symbols to eliminate the influence of small deformation. At the same time, we propose a deformation formula to determine the larger deformation symbols to be evaluated. Secondly, we propose a defect detection method, define the concept of defect cluster and key position, and obtain the two main influencing factors of quality assessment: the inherent characteristics of defects and whether the location of defects is critical. Finally, we define a reasonable scoring strategy based on the above characteristics. This quality evaluation method is an objective evaluation method, and its advantages are: (1) on the premise of only one reference image, it has good robustness when evaluating the quality of images with deformation; (2) The method focuses on the structure quality evaluation of image symbols rather than that of the image itself, so the evaluation results are objective and conform to human's actual feeling for symbol contents. The experimental data of an actual production line demonstrates the validity of the proposed method.