Title
Natural Versus Artificial Scene Classification by Ordering Discrete Fourier Power Spectra
Abstract
Holistic representations of natural scenes is an effective and powerful source of information for semantic classification and analysis of arbitrary images. Recently, the frequency domain has been successfully exploited to holistically encode the content of natural scenes in order to obtain a robust representation for scene classification. In this paper, we present a new approach to naturalness classification of scenes using frequency domain. The proposed method is based on the ordering of the Discrete Fourier Power Spectra. Features extracted from this ordering are shown sufficient to build a robust holistic representation for Natural vs. Artificial scene classification. Experiments show that the proposed frequency domain method matches the accuracy of other state-of-the-art solutions.
Year
DOI
Venue
2008
10.1007/978-3-540-89689-0_18
SSPR/SPR
Keywords
Field
DocType
proposed frequency domain method,natural scene,frequency domain,natural versus artificial scene,scene classification,robust representation,robust holistic representation,semantic classification,ordering discrete fourier power,naturalness classification,holistic representation
Frequency domain,ENCODE,Computer vision,Pattern recognition,Computer science,Naturalness,Scene statistics,Spectral density,Artificial intelligence,Discrete Fourier transform,Visual Word
Conference
Volume
ISSN
Citations 
5342
0302-9743
4
PageRank 
References 
Authors
0.46
4
4
Name
Order
Citations
PageRank
Giovanni Maria Farinella141257.13
Sebastiano Battiato265978.73
G. Gallo322320.06
Roberto Cipolla49413827.88