| dc.contributor | 資訊系 | |
| dc.creator (作者) | 彭彥璁 | |
| dc.creator (作者) | Lai, Tsung-Yueh;Wang, I-Chau;Lee, Yin-Kuan;Lien, Wei-Cheng;Peng, Yan-Tsung;Chen, Kuan-Chun;Chen, Yuan-Te;Chuang, Ya-Ping;Cheng, Yu-Ping;Lin, Ya-Chi;Shie, Pei-Hung | |
| dc.date (日期) | 2026-03 | |
| dc.date.accessioned | 8-Sep-2026 15:06:31 (UTC+8) | - |
| dc.date.available | 8-Sep-2026 15:06:31 (UTC+8) | - |
| dc.date.issued (上傳時間) | 8-Sep-2026 15:06:31 (UTC+8) | - |
| dc.identifier.uri (URI) | https://ah.lib.nccu.edu.tw/item?item_id=184852 | - |
| dc.description.abstract (摘要) | As document forgery schemes become increasingly sophisticated, organizations face mounting challenges in authenticating seals found on official documents. In this study, we collaborated with law enforcement agencies in Taiwan to develop an AI-driven system that supports the rapid identification of forged seals. Instead of relying on manual inspection, the system leverages deep neural networks to analyze overall and fine visual features of seal images. By integrating advanced image enhancement, similarity measurement, and feature comparison modules, the system efficiently filters and ranks potential matches from a dedicated police database. Evaluation on a dataset containing several hundred forged seal images demonstrates that the system achieves greater than 90% accuracy for detecting counterfeit seals. The solution not only reduces the time and effort required for verification but also provides investigators with immediate access to relevant case histories, thereby strengthening the overall fraud prevention workflow. | |
| dc.format.extent | 105 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | The 2025 IEEE International Conference on Computation, Big-Data and Engineering (ICCBE), TAR UMT; IEEE; National Penghu University of Science and Technology, pp.1-12 | |
| dc.subject (關鍵詞) | financial fraud; AI; forged seal recognition; image retrieval system; feature matching | |
| dc.title (題名) | Multi-Level Feature-Matching System for Counterfeit Seal Image Recognition | |
| dc.type (資料類型) | conference | |
| dc.identifier.doi (DOI) | 10.3390/engproc2026128034 | |
| dc.doi.uri (DOI) | https://doi.org/10.3390/engproc2026128034 | |
