Open AccessSequence images hiding technique of three-dimensional object based on principal component analysis in wavelet domain
Author(s) -
Shuai Wen-Juan,
Shuai Feng,
Nie Shou-Ping,
Zhuqing Zhu
Publication year - 2011
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.60.034203
Subject(s) - wavelet , artificial intelligence , principal component analysis , computer science , object (grammar) , computer vision , pattern recognition (psychology) , domain (mathematical analysis) , image (mathematics) , sequence (biology) , wavelet transform , mathematics , mathematical analysis , biology , genetics
In order to hide sequence images of 3D object in a carrying image, eigenimages are obtained by using principal component analysis method. Wavelet coefficients of eigenimages are embedded into the wavelet domain of the carrying image. Based on the relationship of extracted eigenimages and coefficients, a series of images are reconstructed. The proposed method does not store the object images directly, but store the eigenimages which contain information of the 3D object. The experimental results show that the features of 3D object are effectively embedded into the carrying image, and the proposed algorithm has a high capacity.