Title :
Learning oriented dictionary for sparse image representation
Author :
Liang, Ruihua ; Cheng, Lizhi ; Chen, Chen
Author_Institution :
Dept. of Math., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
A novel oriented dictionary is proposed for sparse image representation. The scheme of dictionary learning combines the double sparsity model and the zero-tree structure in the wavelet domain. The dictionary atoms are constructed by grouping the wavelet bases in all high-frequency subbands of the same orientation across different scales. This scheme overcomes the limit on the input signal dimension as well as the over-fitting problem. We demonstrate the potential of the proposed dictionary for M-term approximation of fingerprint images.
Keywords :
fingerprint identification; image representation; wavelet transforms; M-term approximation; dictionary atoms; double sparsity model; fingerprint images; oriented dictionary learning; sparse image representation; wavelet domain; zero-tree structure; Dictionaries; Matching pursuit algorithms; Training; Vectors; Wavelet domain; Wavelet transforms; dictionary learning; sparse representation; subbands; wavelet; zero-tree;
Conference_Titel :
Electronics, Communications and Control (ICECC), 2011 International Conference on
Conference_Location :
Ningbo
Print_ISBN :
978-1-4577-0320-1
DOI :
10.1109/ICECC.2011.6067665
