Open AccessApplication of phase features in recognizing 3-D objects
Author(s) -
Jing Shen,
Xianguo Li,
Shengjiang Chang,
Yanxin Zhang
Publication year - 2005
Publication title -
wuli xuebao
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.