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Biometric identification through hand geometry

Hashemi, J ; Sharif University of Technology | 2005

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  1. Type of Document: Article
  2. DOI: 10.1109/eurcon.2005.1630119
  3. Publisher: IEEE Computer Society , 2005
  4. Abstract:
  5. A new approach for person identification based on hand geometry is presented. After preprocessing hand features are extracted from a photograph taken while user has placed his/her hand (either left or right) on the platform of a document scanner with no limits or fixation. Different pattern recognition techniques like Gaussian mixture modeling (GMM), Radial basis function neural networks (RBF), Multi layer perceptron (MLP), k-Nearest Neighbor (k-NN), Bayes method and mahalanobis/Hamming distance have been used in classification section. Experimental results show a rate of success above 90%. © 2005 IEEE
  6. Keywords:
  7. Computer simulation ; Feature extraction ; Image processing ; Multilayer neural networks ; Pattern recognition ; Radial basis function networks ; Scanning ; Gaussian mixture modeling (GMM) ; Hand geometry ; K-Nearest Neighbor (k-NN) ; Person identification ; Biometrics
  8. Source: EUROCON 2005 - The International Conference on Computer as a Tool, Belgrade, 21 November 2005 through 24 November 2005 ; Volume II , 2005 , Pages 1011-1014 ; 142440049X (ISBN); 9781424400492 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/1630119