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To address this challenge, a novel feature extraction method has been proposed within the traditional image processing framework. This technique is specifically designed for scenarios with limited training data, aiming to enhance performance and efficiency in such conditions. Inspired by image separation algorithms and multifeature fusion strategies, the proposed approach employs guided filtering combined with the Sobel gradient operator to decompose the original finger vein image into a foreground layer and a background layer. Texture features are extracted from the foreground layer, while structural features are derived from the background layer, resulting in two complementary feature maps that capture multidimensional information. These maps are then encoded into a unified one\u2010dimensional feature vector using block\u2010wise histogram descriptors, which enhances feature representation and ensures translation invariance. By separately extracting and effectively fusing multilevel features, the method significantly alleviates the impact of noise on feature extraction and discriminative performance. Without relying on large\u2010scale data, it improves the robustness and practicality of finger vein recognition. Extensive experiments on public datasets validate the effectiveness and generalization capability of the proposed approach.<\/jats:p>","DOI":"10.1155\/cplx\/9965155","type":"journal-article","created":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T04:50:12Z","timestamp":1757307012000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Finger Vein Recognition Framework Using Foreground\u2013Background Decomposition and Translation\u2010Invariant Encoding"],"prefix":"10.1155","volume":"2025","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-6806-4754","authenticated-orcid":false,"given":"Xue","family":"Jiang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-8418-7875","authenticated-orcid":false,"given":"Min","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,9,7]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/1879746"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.3390\/info9090213"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2021.10.004"},{"key":"e_1_2_9_4_2","doi-asserted-by":"crossref","unstructured":"DevR.andKhanamR. 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