基于小波域上质量参数特征的图像拼接篡改盲检测
Image Splicing Detection Based on Image Quality Metrics
DOI: 10.12677/JISP.2018.73015, PDF,    国家自然科学基金支持
作者: 张喆葳, 杨正洪：中国农业大学，数学与应用数学系，北京；牛少彰*：北京邮电大学，智能通信软件与多媒体北京重点实验室，北京
关键词: 离散小波变换；图像质量参数；支持向量机；图像拼接检测；Discrete Wavelet Transform (DWT)； Support Vector Machine (SVM)； Image Splicing Detection； Image Quality Metrics (IQMs)
摘要: 图像拼接是一种常见的图像篡改手段。对拼接过的图像进行盲检测可以有效鉴别图像是否经过人为篡改。针对图像盲检测中经常用到的质量参数特征进行了改进：首先对图像进行离散小波变换，然后提取小波变换后的四个子波带的质量参数特征；最后将得到的特征输入到支持向量机(SVM)中进行分类。在哥伦布比亚图像拼接评测彩色库上进行试验，证明了小波域上的质量参数特征比之前的质量参数特征有更好的表现，达到了93.39%的识别率。
Abstract: Image splicing is a common way of image tampering. Detecting the spliced images blindly can identify whether the image is tampered artificially. The Image Quality Metrics used in image blind detection is improved. First, the image is transformed by discrete wavelet transform, then the quality parameters of the four wavelet bands after wavelet transform are extracted. Finally, the features are input to the support vector machine (SVM) for classification. Experiments on Columbia image splicing detection evaluation database show that the characteristics of the quality pa-rameters in the wavelet domain are better than the previous quality parameters, and the recogni-tion rate of 93.39% is achieved.
文章引用：张喆葳, 杨正洪, 牛少彰. 基于小波域上质量参数特征的图像拼接篡改盲检测[J]. 图像与信号处理, 2018, 7(3): 128-135. https://doi.org/10.12677/JISP.2018.73015

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