Technical Program

Paper Detail

Paper:	IMDSP-L7.5
Session:	Feature Extraction and Analysis
Time:	Thursday, May 18, 11:20 - 11:40
Presentation:	Lecture
Topic:	Image and Multidimensional Signal Processing: Feature Extraction and Analysis
Title:	On Discrimination Between Photorealistic and Photographic Images
Authors:	Ying Wang, Pierre Moulin, University of Illinois at Urbana-Champaign, United States
Abstract:	This paper presents a classifier built for differentiating digital photorealistic images from digital photographs. Results show that our 144-dimensional (144-D) feature vector extracted from characteristic functions of wavelet histograms is more efficient than Lyu and Farid's 216-D feature vector, and Ng et al.'s 192-D feature vector. Our classifier outperforms Lyu and Farid's state-of-art method while only requiring half of their feature extraction and testing time.