JPEG图像中接缝雕刻的检测

Wen-Lung Chang, T. Shih, Hui-Huang Hsu
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引用次数: 19

摘要

内容感知图像重定位算法用于将图像大小修改为不同设备中的合适大小。“接缝雕刻”是一种内容感知的图像重定向算法。本文基于块伪影特征矩阵(BACM),提出了一种无需了解原始图像即可检测自然图像中接缝雕刻的方法。对于原始JPEG图像,BACM呈现规则的对称形状;对于被破坏的图像,破坏了BACM的规则对称特性。在从图像中发现BACM后,定义18个特征来检测BACM的损伤,训练支持向量机(SVM)分类器来识别图像是原始图像还是被缝切修改过。结果表明,BACM算法可用于检测JPEG格式图像的缝切损伤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of seam carving in JPEG images
The content-aware image retargeting algorithm is used for modifying the image size into the suitable size in different device. "Seam carving" is a kind of content aware image retargeting algorithm. In this paper, based on the blocking artifact characteristics matrix (BACM), we propose a method to detect seam carving in natural images without knowledge of the original image. In detail, for the original JPEG images, the BACM exhibits regular symmetrical shapes; for the images that are damaged, the regular symmetrical property of the BACM is destroyed. After found BACM from images, we define 18 features to detect the damage from BACM to train a support vector machine (SVM) classifier for recognizing whether an image is an original or it has been modified by seam-carving. We show that BACM is useful for detect the damage by seam-carving in JPEG format images.
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