A local DCT-2 feature extraction approach for personal identification based on palmprint
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- Choge H. Kipsang
- The University of Tokushima
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- Oyama Tadahiro
- Kobe City College of Technology
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- Karungaru Stephen
- The University of Tokushima
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- Tsuge Satoru
- Daido University
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- Fukumi Minoru
- The University of Tokushima
書誌事項
- タイトル別名
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- A Local DCT-II Feature Extraction Approach for Personal Identification Based on Palmprint
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説明
Biometric applications based on the palmprint have recently attracted increased attention from various researchers. In this paper, a method is presented that differs from the commonly used global statistical and structural techniques by extracting and using local features instead. The middle palm area is extracted after preprocessing for rotation, position and illumination normalization. The segmented region of interest is then divided into blocks of either 8×8 or 16×16 pixels in size. The type-II Discrete Cosine Transform (DCT) is applied to transform the blocks into DCT space. A subset of coefficients that encode the low to medium frequency components is selected using the JPEG-style zigzag scanning method. Features from each block are subsequently concatenated into a compact feature vector and used in palmprint verification experiments with palmprints from the PolyU Palmprint Database. Results indicate that this approach achieves better results than many conventional transform-based methods, with an excellent recognition accuracy above 99% and an Equal Error Rate (EER) of less than 1.2% in palmprint verification.
収録刊行物
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- 電気学会論文誌C(電子・情報・システム部門誌)
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電気学会論文誌C(電子・情報・システム部門誌) 130 (9), 1657-1666, 2010
一般社団法人 電気学会
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詳細情報 詳細情報について
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- CRID
- 1390282679586217216
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- NII論文ID
- 10026580001
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- NII書誌ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL書誌ID
- 10800326
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可