Color image copy tampering detection method based on local quaternion exponent moments

A quaternion exponent moment and color image technology, applied in the field of image processing, can solve the problems of unsatisfactory detection of tampered areas and large algorithm time complexity

Inactive Publication Date: 2018-12-07
LIAONING NORMAL UNIVERSITY
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Problems solved by technology

The tamper detection algorithm based on block matching has high detection accuracy for tampered images, but the time complexity of the whole algorithm is very large; the tamper detection algorithm based on feature point matching greatly reduces the time complexity, but for smooth The detection effect of the tampered area is not very ideal

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  • Color image copy tampering detection method based on local quaternion exponent moments
  • Color image copy tampering detection method based on local quaternion exponent moments
  • Color image copy tampering detection method based on local quaternion exponent moments

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Embodiment Construction

[0052] A color image copy tampering detection method based on local quaternion exponential moments, according to the following steps:

[0053] Step 1: Use the entropy-based super pixel segmentation algorithm combined with the non-subsampled Shearlet transform to perform adaptive super pixel block for the image to be detected after the Gaussian smoothing filter preprocessing, as follows:

[0054] Step 11: Read the image to be inspected and preprocess it with Gaussian smoothing filter to remove noise;

[0055] Step 12: Perform non-downsampling Shearlet transform on the image obtained after preprocessing in Step 11, and initialize the number of superpixel blocks adaptively;

[0056] Step 121: Read the pre-processed image and perform four-level non-down-sampling Shearlet change to calculate the proportion of low-frequency energy to the total energy, where Represents low frequency energy, Represents high frequency energy, Indicates the proportion of low-frequency energy to the total ener...

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Abstract

The invention discloses a color image tamper detection method based on local quaternion index moment through which algorithm time complexity can be greatly reduced and a replication tamper area can be accurately detected. Self-adaptive super-pixel partitioning is performed on an image to be detected after Gaussian smoothing filtering preprocessing by utilizing a super-pixel segmentation algorithm based on entropy rate with combination of non-subsample Shearlet transform; the quaternion index moment is utilized to express Sifer feature point local area features and similar block matching is performed on all the Sifer feature point local area features of each super-pixel block; a suspected tamper area is determined by utilizing the matching feature points in the similar blocks obtained in the step 2; and the replication tamper area is marked by utilizing morphological filtering operation.

Description

Technical field [0001] The invention belongs to the field of image processing, in particular to a color image copy tampering detection method based on local quaternion exponential moments that can greatly reduce the time complexity of the algorithm and accurately detect the tampered area. Background technique [0002] Image area copying and tampering is a typical and effective way of image forgery. It is to copy and paste an area in the image to disjoint areas of the same image, so as to eliminate or hide an object or area of ​​the image. . Normally, when performing regional copy tampering on images, post-processing operations are artificially added to the tampered area, such as Gaussian noise, Gaussian blur, double JPEG compression, etc., making it difficult for the human eye to detect. Most tampered images are also mixed to tampering The area is subjected to geometric attack operations such as rotation and zooming, which changes the perspective effect of the copied area, makin...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/90
CPCG06T2207/20021
Inventor 王向阳刘宇男牛盼盼
Owner LIAONING NORMAL UNIVERSITY
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