Journal of Computer Applications
• Graphics and image processing • Previous Articles Next Articles
Zhen ZHANG Jiquan Kang Xijian Ping Yuan Ren
Received:
Revised:
Online:
Published:
Contact:
张震 康吉全 平西建 任远
通讯作者:
Abstract: Image splicing is a technique commonly used in image tampering. To implement image splicing blind detection,a new splicing detection scheme was proposed. Image splicing detection could be regarded as a two-class pattern recognition problem and the model was established based on moment features and some Image Quality Metrics (IQMs) extracted from the given test image. This model could measure statistical differences between original image and spliced image. Kernel-based Support Vector Machine (SVM) was chosen as a classifier to train and test the given images. Experimental results demonstrate that this new splicing detection scheme has some advantages of high-accuracy and wide-application.
Key words: blind image forensics, image splicing detection, image quality metrics (IQMs), moment features, Support Vector Machine (SVM)
摘要: 图像拼接是一种常见的图像篡改手段。为了对拼接的数字图像实施盲检测,提出一种新的拼接图像的检测方法。借用二分类的模式识别概念,使用图像质量评价量和矩特征量来建立模型,以捕获原始图像和拼接图像之间的统计差异,选用支持向量机作为分类器进行训练和测试,对拼接图像的盲检测进行了研究。实验结果表明,该方法具有精确度高、应用面广的优点。
关键词: 数字图像盲取证, 图像拼接检测, 图像质量评价量, 矩特征量, 支持向量机
Zhen ZHANG Jiquan Kang Xijian Ping Yuan Ren. Blind detection of image splicing based on image quality metrics and moment features[J]. Journal of Computer Applications.
张震 康吉全 平西建 任远. 用统计特征量实现的图像拼接盲检测[J]. 计算机应用.
0 / Recommend
Add to citation manager EndNote|Ris|BibTeX
URL: http://www.joca.cn/EN/
http://www.joca.cn/EN/Y2008/V28/I12/3108