| Gaussian multiscale aggregation applied to segmentation in hand biometrics. | |
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MedLine Citation:
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PMID: 22247658 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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This paper presents an image segmentation algorithm based on Gaussian multiscale aggregation oriented to hand biometric applications. The method is able to isolate the hand from a wide variety of background textures such as carpets, fabric, glass, grass, soil or stones. The evaluation was carried out by using a publicly available synthetic database with 408,000 hand images in different backgrounds, comparing the performance in terms of accuracy and computational cost to two competitive segmentation methods existing in literature, namely Lossy Data Compression (LDC) and Normalized Cuts (NCuts). The results highlight that the proposed method outperforms current competitive segmentation methods with regard to computational cost, time performance, accuracy and memory usage. |
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Authors:
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Alberto de Santos Sierra; Carmen Sánchez Avila; Javier Guerra Casanova; Gonzalo Bailador del Pozo |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't Date: 2011-11-28 |
Journal Detail:
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Title: Sensors (Basel, Switzerland) Volume: 11 ISSN: 1424-8220 ISO Abbreviation: Sensors (Basel) Publication Date: 2011 |
Date Detail:
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Created Date: 2012-02-07 Completed Date: 2012-06-29 Revised Date: 2013-05-29 |
Medline Journal Info:
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Nlm Unique ID: 101204366 Medline TA: Sensors (Basel) Country: Switzerland |
Other Details:
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Languages: eng Pagination: 11141-56 Citation Subset: IM |
Affiliation:
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Group of Biometrics, Biosignals and Security, Universidad Politécnica de Madrid, Campus de Montegancedo s/n, 28223 Pozuelo de Alarcón, Madrid, Spain. alberto@cedint.upm.es |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Biometry* Hand* Humans |
| Comments/Corrections | |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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