期刊
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
卷 48, 期 -, 页码 281-291出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jvcir.2017.07.006
关键词
Image forensics; Content-aware image retargeting; Seam carving; Low scaling ratios; Spatial and frequency entropy; Object removal
资金
- National Natural Science Foundation of China [61572183, 61379143, 61672222]
- Scientific Research Fund of Hunan Provincial Education Department of China [15C0083, 14C0029]
- Natural Science Foundation of Hunan Province [2016JJ2005, 2017JJ2291]
Seam carving is the most popular content-aware image retargeting technique. However, it may also be used to correct poor photo composition in photography competition or to remove object from image for malicious purpose. A blind detection approach is presented for seam carved image with low scaling ratio (LSR). It exploits spatial and spectral entropies (SSE) on multi-scale images (candidate image and its down-sampled versions). We observe that when a few seams are deleted from an original image, its SSE distribution is greatly changed. Forty-two features are designed to unveil the statistical properties of SSE in terms of centralized tendency, dispersion tendency and distribution tendency. They are combined with the local binary pattern (LBP)-based energy features to form ninety-six features. Finally, support vector machine (SVM) is exploited as classifier to determine whether an image is original or suffered from seam carving. Experimental results show that the proposed approach achieves superior detection accuracy over the state-of-the-art works, especially for resized image by seam carving with LSRs. Moreover, it is robust against JPEG compression and seam insertion. (C) 2017 Elsevier Inc. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据