期刊
MULTIMEDIA TOOLS AND APPLICATIONS
卷 76, 期 1, 页码 333-354出版社
SPRINGER
DOI: 10.1007/s11042-015-3058-7
关键词
Biometric fusion systems; Dual-source discrimination power analysis; Multi-instance contactless palmprint recognition; Feature level fusion; Two-dimensional discrete cosine transform
类别
资金
- National Natural Science Foundation of China [61305010, 61262019]
- Voyage Project of Jiangxi Province [201450]
- Doctoral Initiating Foundation of Nanchang Hangkong University [EA201308058]
- Foundation of Sichuan Development Research Center of Cultural Industries [WHCY2014A9]
- Key Foundation of Xihua University
- Basic Science Research Program Through the National Research Foundation of Korea (NRF) by the Ministry of Education, Science Technology [20120192]
Due to the benefits of palmprint recognition and the advantages of biometric fusion systems, it is necessary to study multi-source palmprint fusion systems. Unfortunately, the research on multi-instance palmprint feature fusion is absent until now. In this paper, we extract the features of left and right palmprints with two-dimensional discrete cosine transform (2DDCT) to constitute a dual-source space. Normalization is utilized in dual-source space to avoid the disturbance caused by the coefficients with large absolute values. Thus complicated pre-masking is needless and arbitrary removing of discriminative coefficients is avoided. Since more discriminative coefficients can be preserved and retrieved with discrimination power analysis (DPA) from dual-source space, the accuracy performance is improved. The experiments performed on contactless palmprint database confirm that dual-source DPA, which is designed for multi-instance palmprint feature fusion recognition, outperforms single-source DPA.
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