中国司法鉴定Issue(3)：55-64,10.DOI:10.3969/j.issn.1671-2072.2026.03.006
基于小样本量的印章印文种类识别研究
Research on Recognition of Stamp Impression Types Based on Small Sample Quantity
摘要
Abstract
Objective To investigate the feasibility of classical computer vision models in recognizing stamp impression types with small sample quantity,as well as the impact of different stamping conditions.Methods Three network models,VGG16,ResNet50,and visual Transformer,were utilized to identify the kinds of stamp impressions imprinted by six common types of stamps,including photosensitive stamp,laser-engraved penetration stamp,self-inking stamp,copper stamp,wooden stamp,and rubber stamp.Results In the experiment,the three network models performed well in recognizing all six types of stamp impressions.The recognition accuracy for photosensitive stamp,self-inking stamp,wooden stamp and rubber stamp all basically reached 100%,while only a slight decrease was observed in the recognition accuracy for laser-engraved penetration stamp and copper stamp.In the following blind test,the recognition accuracy of the three models for the six types of stamp impressions generally dropped by 3 to 35 percentage points,confirming the limitations of the network models in real complex scenarios.Conclusion Classical models in the field of computer vision can assist in recognizing the types of stamp impressions,but their recognition accuracy needs to be improved.关键词
文件检验/印章印文检验/种类识别/卷积神经网络/视觉TransformerKey words
document examination/examination of stamp impression/type recognition/convolutional neural network/visual Transformer分类
社会科学引用本文复制引用
陈琦,李冰,张磊,黄旭..基于小样本量的印章印文种类识别研究[J].中国司法鉴定,2026,(3):55-64,10.基金项目
最高人民检察院检察技术信息研究中心基本科研项目(JBKY20241002) （JBKY20241002）
广东省证据材料司法鉴定(南天)工程技术研究中心开放课题基金项目(ETRC202306) （南天）
中央高校基本科研业务费专项资金资助项目. （）
