抄録
Barcodes and 2D codes are widely used for various purposes, such as electronic payments and product management. Special code readers, and consumer smartphones can be used to scan codes; thus concerns about fraud and authenticity are important. Embedding watermarks in 2D codes, which allows simultaneous recognition and tamper detection by simply analyzing the captured pattern without requiring an additional device is considered a promising solution. However, smartphone cameras frequently suffer misfocus especially if the target object is too close to the lens, which makes the captured image defocused and results in failure to read watermarks. In this paper, we propose the use of a coded aperture imaging technique to recover watermarks. We have designed a coded aperture that is robust against defocus blur by optimizing the aperture pattern using a genetic algorithm. In addition, we have developed a programmable coded aperture that includes an actual optical process that works in an optimization loop; thus, the complicated effects of the optical aberrations can be considered. Experimental results demonstrate that the proposed method can extend the depth of field for watermark extraction to 3.1 times wider than that of a general circular aperture.
| 元の言語 | 英語 |
|---|---|
| ホスト出版物のタイトル | Computer Vision – ACCV 2018 - 14th Asian Conference on Computer Vision, Revised Selected Papers |
| 編集者 | Greg Mori, C.V. Jawahar, Konrad Schindler, Hongdong Li |
| 出版者 | Springer Verlag |
| ページ | 231-246 |
| ページ数 | 16 |
| ISBN（印刷物） | 9783030208752 |
| DOI | |
| 出版物ステータス | 出版済み - 1 1 2019 |
| イベント | 14th Asian Conference on Computer Vision, ACCV 2018 - Perth, オーストラリア 継続期間: 12 2 2018 → 12 6 2018 |
出版物シリーズ
| 名前 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| 巻 | 11366 LNCS |
| ISSN（印刷物） | 0302-9743 |
| ISSN（電子版） | 1611-3349 |
会議
| 会議 | 14th Asian Conference on Computer Vision, ACCV 2018 |
|---|---|
| 国 | オーストラリア |
| 市 | Perth |
| 期間 | 12/2/18 → 12/6/18 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
これを引用
A Coded Aperture for Watermark Extraction from Defocused Images. / Hamasaki, Hiroki; Takeshita, Shingo; Nakai, Kentaro; Sonoda, Toshiki; Kawasaki, Hiroshi; Nagahara, Hajime; Ono, Satoshi.
Computer Vision – ACCV 2018 - 14th Asian Conference on Computer Vision, Revised Selected Papers. 版 / Greg Mori; C.V. Jawahar; Konrad Schindler; Hongdong Li. Springer Verlag, 2019. p. 231-246 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻 11366 LNCS).研究成果: 著書/レポートタイプへの貢献 › 会議での発言
}
TY - GEN
T1 - A Coded Aperture for Watermark Extraction from Defocused Images
AU - Hamasaki, Hiroki
AU - Takeshita, Shingo
AU - Nakai, Kentaro
AU - Sonoda, Toshiki
AU - Kawasaki, Hiroshi
AU - Nagahara, Hajime
AU - Ono, Satoshi
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Barcodes and 2D codes are widely used for various purposes, such as electronic payments and product management. Special code readers, and consumer smartphones can be used to scan codes; thus concerns about fraud and authenticity are important. Embedding watermarks in 2D codes, which allows simultaneous recognition and tamper detection by simply analyzing the captured pattern without requiring an additional device is considered a promising solution. However, smartphone cameras frequently suffer misfocus especially if the target object is too close to the lens, which makes the captured image defocused and results in failure to read watermarks. In this paper, we propose the use of a coded aperture imaging technique to recover watermarks. We have designed a coded aperture that is robust against defocus blur by optimizing the aperture pattern using a genetic algorithm. In addition, we have developed a programmable coded aperture that includes an actual optical process that works in an optimization loop; thus, the complicated effects of the optical aberrations can be considered. Experimental results demonstrate that the proposed method can extend the depth of field for watermark extraction to 3.1 times wider than that of a general circular aperture.
AB - Barcodes and 2D codes are widely used for various purposes, such as electronic payments and product management. Special code readers, and consumer smartphones can be used to scan codes; thus concerns about fraud and authenticity are important. Embedding watermarks in 2D codes, which allows simultaneous recognition and tamper detection by simply analyzing the captured pattern without requiring an additional device is considered a promising solution. However, smartphone cameras frequently suffer misfocus especially if the target object is too close to the lens, which makes the captured image defocused and results in failure to read watermarks. In this paper, we propose the use of a coded aperture imaging technique to recover watermarks. We have designed a coded aperture that is robust against defocus blur by optimizing the aperture pattern using a genetic algorithm. In addition, we have developed a programmable coded aperture that includes an actual optical process that works in an optimization loop; thus, the complicated effects of the optical aberrations can be considered. Experimental results demonstrate that the proposed method can extend the depth of field for watermark extraction to 3.1 times wider than that of a general circular aperture.
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UR - http://www.scopus.com/inward/citedby.url?scp=85066937452&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-20876-9_15
DO - 10.1007/978-3-030-20876-9_15
M3 - Conference contribution
AN - SCOPUS:85066937452
SN - 9783030208752
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 231
EP - 246
BT - Computer Vision – ACCV 2018 - 14th Asian Conference on Computer Vision, Revised Selected Papers
A2 - Mori, Greg
A2 - Jawahar, C.V.
A2 - Schindler, Konrad
A2 - Li, Hongdong
PB - Springer Verlag
ER -