DocumentCode :
2495094
Title :
Assessing the naturalness of scenes: An approach using statistics of local features
Author :
Deng, Jeremiah D. ; Brinkworth, Russell SA ; Carroll, David C O
Author_Institution :
Dept. of Inf. Sci., Univ. of Otago, Dunedin
fYear :
2008
fDate :
26-28 Nov. 2008
Firstpage :
1
Lastpage :
6
Abstract :
What statistics makes an image of natural scene different from that of an urban or artificial environment? This has been an intriguing research topic in recent years. In this paper, in contrast to the more popular approach of using global frequency spectral features, we propose to employ a few statistics measures derived from local edge and fractal features. Feature selection methods are used to reveal the relevance of the defined features. The effectiveness of the proposed feature scheme is demonstrated using benchmark digital image data as well as high dynamic range image data.
Keywords :
computer vision; edge detection; feature extraction; fractals; image classification; natural scenes; statistics; artificial environment; computer vision; edge feature selection; fractal feature selection; global frequency spectral feature; local feature statistics measure; natural scene image classification; urban environment; Digital images; Dynamic range; Feature extraction; Fractals; Frequency; Histograms; Insects; Layout; Object detection; Statistics; classification; feature selection; fractal; natural scenes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Vision Computing New Zealand, 2008. IVCNZ 2008. 23rd International Conference
Conference_Location :
Christchurch
Print_ISBN :
978-1-4244-3780-1
Electronic_ISBN :
978-1-4244-2583-9
Type :
conf
DOI :
10.1109/IVCNZ.2008.4762129
Filename :
4762129
Link To Document :
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