抄録
This paper proposes a method to uniquely identify commercial products with an item level barcode, specifically JAN/EAN/UCC, with which we usually cannot distinguish individual products. This research is motivated by the industrial and consumer needs for first-in-first-out operations of their inventories in the environment, where serial level barcodes, such as GS1-128 and SGTIN, or RFID are still not available. The proposal, referred to as Barcode Fingerprinting, utilizes the microscopic features of printed barcode stripes to discriminate each other. We zoom in a particular portion of a barcode image and apply SURF Algorithms and RANSAC Algorithms, to extract the microscopic features. The features are stored with the barcode ID and the time stamp for the future comparisons. We examined the feasibility of the proposal method by processing 100 barcodes of single brand PET bottles. The experiment reveals that we can uniquely identify each of the 100 barcodes by using Barcode Fingerprinting with a proper preprocessing of images.
| 本文言語 | English |
|---|---|
| ホスト出版物のタイトル | IEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings |
| 出版社 | Institute of Electrical and Electronics Engineers Inc. |
| ページ | 416-420 |
| ページ数 | 5 |
| 巻 | 2018-January |
| ISBN（電子版） | 9781467399449 |
| DOI | |
| 出版ステータス | Published - 2018 5 4 |
| イベント | 4th IEEE World Forum on Internet of Things, WF-IoT 2018 - Singapore, Singapore 継続期間: 2018 2 5 → 2018 2 8 |
Other
| Other | 4th IEEE World Forum on Internet of Things, WF-IoT 2018 |
|---|---|
| Country | Singapore |
| City | Singapore |
| Period | 18/2/5 → 18/2/8 |
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture
- Information Systems and Management
- Safety, Risk, Reliability and Quality