基于图像质量评价量和隐马尔科夫模型的图像拼接检测

Blind Detection of Image Splicing Based on Image Quality Metrics and Hidden Markov Model

  • 摘要: 基于对图像拼接技术的分析,提出了基于图像质量评价量和隐马尔科夫模型(hidden Markov model,HMM)的拼接图像检测方法,提取了图像的特征值,使用支持向量机(support vector machine,SVM)对特征值进行训练和分类,得到了较好的效果。

     

    Abstract: In order to implement image splicing blind detection,a new splicing detection scheme is proposed based on the model consisting of features from hidden Markov model and some image quality metrics(IQMs) extracted from the given test image,which are sensitive to spliced image.This model can measure statistical differences between original image and spliced image.Kernel-based support vector machine(SVM) is chosen as a classifier to train and test the given image.Experimental results show that the new splicing detection scheme has some advantages of highaccuracy and widelapplication.

     

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