Palm Vein Recognition Based on NPE and KELM
Palm veins have become a research hotspot of biometric recognition due to their own advantages of universality, uniqueness, collectability and stability. This paper proposes a palm vein recognition algorithm based on Neighborhood Preserving Embedding (NPE) and Kernel Extreme Learning Machine (KELM)....
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9429244/ |
| _version_ | 1818361679044411392 |
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| author | Saisai Sun Xiaoyan Cong Ping Zhang Bo Sun Xiumei Guo |
| author_facet | Saisai Sun Xiaoyan Cong Ping Zhang Bo Sun Xiumei Guo |
| author_sort | Saisai Sun |
| collection | DOAJ |
| description | Palm veins have become a research hotspot of biometric recognition due to their own advantages of universality, uniqueness, collectability and stability. This paper proposes a palm vein recognition algorithm based on Neighborhood Preserving Embedding (NPE) and Kernel Extreme Learning Machine (KELM). The algorithm firstly performs gray-scale normalization processing on vein images, then extracts neighborhood preserving embedding dimensionality reduction features, and finally uses extreme learning machine for classification and recognition. The method is tested on the multispectral palmprint database of Hong Kong Polytechnic University. The experimental results show that this method can effectively reduce the vein dimensions to less than 30, and achieve an ideal recognition effect, if the parameters are selected appropriately. The algorithm is also verified on the palmvein database of Tongji University and FYO palmvein database for verifying the robustness, and also get ideal experimental results. |
| first_indexed | 2024-12-13T21:20:31Z |
| format | Article |
| id | doaj.art-0e9dc6fcc00d4f4ba24b7f201b774e02 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T21:20:31Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-0e9dc6fcc00d4f4ba24b7f201b774e022022-12-21T23:31:07ZengIEEEIEEE Access2169-35362021-01-019717787178310.1109/ACCESS.2021.30794589429244Palm Vein Recognition Based on NPE and KELMSaisai Sun0Xiaoyan Cong1Ping Zhang2Bo Sun3Xiumei Guo4https://orcid.org/0000-0002-4953-5554College of Medical Information Engineering, Shandong First Medical University and Shandong Academy of Medical Science, Tai’an, ChinaCollege of Information Science and Engineering, Shandong Agricultural University, Tai’an, ChinaCollege of Information Science and Engineering, Shandong Agricultural University, Tai’an, ChinaCollege of Information Science and Engineering, Shandong Agricultural University, Tai’an, ChinaCollege of Information Science and Engineering, Shandong Agricultural University, Tai’an, ChinaPalm veins have become a research hotspot of biometric recognition due to their own advantages of universality, uniqueness, collectability and stability. This paper proposes a palm vein recognition algorithm based on Neighborhood Preserving Embedding (NPE) and Kernel Extreme Learning Machine (KELM). The algorithm firstly performs gray-scale normalization processing on vein images, then extracts neighborhood preserving embedding dimensionality reduction features, and finally uses extreme learning machine for classification and recognition. The method is tested on the multispectral palmprint database of Hong Kong Polytechnic University. The experimental results show that this method can effectively reduce the vein dimensions to less than 30, and achieve an ideal recognition effect, if the parameters are selected appropriately. The algorithm is also verified on the palmvein database of Tongji University and FYO palmvein database for verifying the robustness, and also get ideal experimental results.https://ieeexplore.ieee.org/document/9429244/Vein recognitionneighborhood preserving embeddingextreme learning machine |
| spellingShingle | Saisai Sun Xiaoyan Cong Ping Zhang Bo Sun Xiumei Guo Palm Vein Recognition Based on NPE and KELM IEEE Access Vein recognition neighborhood preserving embedding extreme learning machine |
| title | Palm Vein Recognition Based on NPE and KELM |
| title_full | Palm Vein Recognition Based on NPE and KELM |
| title_fullStr | Palm Vein Recognition Based on NPE and KELM |
| title_full_unstemmed | Palm Vein Recognition Based on NPE and KELM |
| title_short | Palm Vein Recognition Based on NPE and KELM |
| title_sort | palm vein recognition based on npe and kelm |
| topic | Vein recognition neighborhood preserving embedding extreme learning machine |
| url | https://ieeexplore.ieee.org/document/9429244/ |
| work_keys_str_mv | AT saisaisun palmveinrecognitionbasedonnpeandkelm AT xiaoyancong palmveinrecognitionbasedonnpeandkelm AT pingzhang palmveinrecognitionbasedonnpeandkelm AT bosun palmveinrecognitionbasedonnpeandkelm AT xiumeiguo palmveinrecognitionbasedonnpeandkelm |