Application of phase features in recognizing 3-D objects | Zendy

Jinyuan Shen | Zendy; Xianguo Li | Zendy; Chang Sheng-Jiang | Zendy; Yanxin Zhang | Zendy

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Application of phase features in recognizing 3-D objects

Author(s) -

Jinyuan Shen,

Xianguo Li,

Chang Sheng-Jiang,

Yanxin Zhang

Publication year - 2005

Publication title -

acta physica sinica

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.199

H-Index - 47

ISSN - 1000-3290

DOI - 10.7498/aps.54.5157

Subject(s) - computer science , artificial neural network , artificial intelligence , digital holography , pattern recognition (psychology) , holography , object (grammar) , phase (matter) , variance (accounting) , computer vision , wavelength , optics , physics , quantum mechanics , accounting , business

A new approach based on phase features combined with neural network model is proposed for recognizing 3-D objects. The phase features of an object were extracted by wavelength-scanning digital holography and numerical reconstruction technique. A BP neural network with one hidden-layer trained by reconstructed images of three pyramids was used to recognize other pyramids with some variance, and the correct recognition rate of these pyramids is up to 100%. The simulation results demonstrate that the method is effective.

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