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Contourlet transform-based image splicing detection method

A detection method and image stitching technology, which are used in image enhancement, image analysis, image data processing, etc.

Inactive Publication Date: 2016-10-26
SUN YAT SEN UNIV
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  • Application Information

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Problems solved by technology

However, due to the rapid development of digital image editing technology, the tampering of digital image content is becoming easier, which brings challenges to the authenticity and security of digital images

Method used

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  • Contourlet transform-based image splicing detection method
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  • Contourlet transform-based image splicing detection method

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Embodiment 1

[0041] Such as figure 1 As shown, an image mosaic detection method based on Contourlet transform includes the following steps:

[0042]S1: Select the image training set: the training set contains the original image without any tampering operation and the stitched image that has been stitched and tampered with. In this example, the IFS-TC image set about digital image stitching detection provided by the IEEE Information Forensics and Security Technical Committee is used. It contains 1050 original images and 1150 stitched images;

[0043] S2: Perform Contourlet transformation on the training image: All images in the IFS-TC image set are color images, and the same Contourlet transformation is performed on each image in the training set, using k-layer Contourlet decomposition, and the corresponding pyramid direction filter for each layer The number of vectors of DFB is set to {f1,f2,...,fn}, each layer of decomposition will get the corresponding {2 f1 ,2 f2 ,…,2 fn} coefficien...

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Abstract

The present invention provides a contourlet transform-based image splicing detection method. Contourlet transform can greatly describe contour and directional texture information in an image. According to the method, contourlet transform is carried out on training images, and then, Markov features are extracted; a support vector machine-based recursive feature elimination (SVM-RFE) method is used to carry out dimensionality reduction on a feature set, so that detection efficiency and accuracy can be improved; optimal parameters are found by using the feature set which has been subjected to dimensionality reduction, so that an SVM classification model can be obtained; corresponding feature vectors are extracted from a test image; and the obtained classification model is adopted to carry out classification prediction on the feature vectors of the test image, so that the result of judgment on whether the test image has been subjected to splicing operation can be obtained. According to the method, feature extraction is carried out in a new transform domain, so that the method has high detection efficiency and accuracy.

Description

technical field [0001] The present invention relates to the technical field of digital image forensics, and more particularly relates to an image splicing detection method based on Contourlet transformation. Background technique [0002] With the popularity of networks and smart devices, the importance of digital images in information dissemination has become increasingly prominent. However, due to the rapid development of digital image editing technology, the tampering of digital image content is becoming more and more easy, which brings challenges to the authenticity and security of digital images. Therefore, how to realize reliable authentication of content authenticity and security in the process of dissemination, sharing and application of digital images has important practical significance. [0003] Image splicing detection is an important branch of digital image forensics technology. Its purpose is to detect whether there is splicing and tampering in digital images, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T3/40
CPCG06T3/4038G06T7/0002G06T2207/20048G06T2207/20081
Inventor 卢伟张清柏
Owner SUN YAT SEN UNIV