Model-guided deformable hand shape recognition without positioning aids

  • Authors:
  • Wei Xiong;Kar-Ann Toh;Wei-Yun Yau;Xudong Jiang

  • Affiliations:
  • Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore;Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore;Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore;School of EEE, Nanyang Technological University, Block S1, 50 Nanyang Avenue, Singapore 639798, Singapore

  • Venue:
  • Pattern Recognition
  • Year:
  • 2005

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Abstract

This work addresses the problem of deformable hand shape recognition in biometric systems without any positioning aids. We separate and recognize multiple rigid fingers under Euclidean transformations. An elliptical model is introduced to represent fingers and accelerate the search of optimal alignments of fingers. Unlike other methods, the similarity is measured during alignment search based on finger width measurements defined at nodes by controllable intervals to achieve balanceable recognition accuracy and computational cost. Technically, our method bridges the traditional handcrafted-feature methods and the shape-distance methods. We have tested it using our 108-person-540-sample database with significantly increased positive recognition accuracy.