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Author Hong Huo ♦ Tao Fang
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2013
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Dictionaries ♦ Feature extraction ♦ Neurons ♦ Training ♦ Sparse matrices ♦ Sociology ♦ Statistics ♦ Texture features extraction ♦ Sparse representation ♦ Pooling ♦ Rotation invariance
Abstract Inspired by the characteristics of sparse representation and pooling in human visual system, Orientation Pooling based on Sparse Representation (OPSR) is proposed to extract sparse and rotation-invariant texture features. At first, we assume that the over-complete dictionary represents a population of neurons in the cerebral cortex, and each atom in it will respond to a stimulus with a specific orientation like the response of a simple cell in the visual cortex. Then, the atoms are rotated at several different angles and added to the dictionary. Thus, atoms in the extended dictionary can respond to stimuli at different orientations. The responses of each atom and its corresponding rotated ones are pooled to obtain rotation-invariant texture features, which simulates the invariant features obtained by pooling the responses to stimuli of different orientations in human visual system. The comparative experiments with several traditional methods on two texture databases are conducted. The results demonstrate that OPSR method can effectively extract texture features with stronger rotation invariance.
Description Author affiliation: Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China (Hong Huo; Tao Fang)
ISBN 9781479928255
ISSN 21593450
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2013-10-22
Publisher Place China
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781479928279
Size (in Bytes) 536.32 kB
Page Count 4
Starting Page 1
Ending Page 4

Source: IEEE Xplore Digital Library