Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Image stitching tampering detection method

An image mosaic and detection method technology, which is applied in the field of image analysis, can solve the problems of tampering targets in areas that are easy to be ignored, and the inability to accurately locate tampered areas in stitched images, etc.

Active Publication Date: 2020-04-28
HEBEI UNIV OF TECH
View PDF11 Cites 26 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The technical problem to be solved by the present invention is to provide a detection method for image mosaic tampering, which is a detection method for image mosaic tampering based on the hybrid domain attention mechanism and the hollow space pyramid pooling module, which overcomes the existing technology based on a specific Assuming that the tampered area of ​​the stitched image cannot be accurately located, it is easy to ignore the defects of the tampered target with a small area in the detection

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Image stitching tampering detection method
  • Image stitching tampering detection method
  • Image stitching tampering detection method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0095] The specific steps of the detection method for image mosaic tampering based on the hybrid domain attention mechanism and the empty space pyramid pooling module in this embodiment are as follows:

[0096] In the first step, the depth feature map F of the input image is extracted:

[0097] Adjust the size of the input image I to 256×256 pixels, and extract the depth feature map F of the input image through the VGG16 deep neural network module, as shown in the following formula (1),

[0098] F=VGG16(Resize(I)) (1),

[0099] In formula (1), VGG16( ) is the VGG16 deep neural network module, and Resize( ) is a function to adjust the size of the input image;

[0100] The above VGG16 deep neural network module includes convolution, hole convolution, Relu, pooling operations,

[0101] The convolution operation is as follows formula (19),

[0102] F_out=(F_in+2pad-k_size) / stride+1 (19),

[0103] In formula (19), F_out is the result after the convolution layer, F_in is the inp...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an image stitching tampering detection method, relates to the field of image analysis, and is an image stitching tampering detection method based on a mixed domain attention mechanism and a cavity space pyramid pooling module, and the method comprises the steps of extracting a depth feature map F of an input image; obtaining a feature map Ffinal of the tampered area by adopting a mixed domain attention mechanism; adopting a cavity space pyramid pooling module to obtain a final positioning mask M; training a stitching tampering detection method based on the mixed domainattention mechanism and the cavity space pyramid pooling module. According to the measurement of image stitching tampering detection based on the mixed domain attention mechanism and the cavity spacepyramid pooling module, the defects that in the prior art, the tampering area of a stitched image cannot be accurately positioned based on a certain specific hypothesis, and a tampering target with asmall area is easily ignored in detection are overcome.

Description

technical field [0001] The technical solution of the present invention relates to the field of image analysis, in particular to a detection method for image splicing and tampering. Background technique [0002] With the rapid development of image editing software such as Photoshop, people can easily modify digital images according to their own wishes, reaching the level of false ones. Such forged images and pictures will distort the truth, cause misunderstandings to the public, and adversely affect the development of society. Therefore, it is necessary to detect forged and tampered images to protect the authenticity and integrity of digital images and avoid misleading, fraud and copyright disputes caused by tampered images. [0003] Stitching is the most common way of image tampering, which is to splicing an object or a certain area in one image into another image, so as to hide or increase an object or a certain area in the image. When stitching different images, post-pro...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06T7/00G06T3/40
CPCG06T3/4038G06T7/0002G06T2207/10028G06T2207/20016G06T2207/20081G06T2207/20084G06T2207/20221
Inventor 阎刚陈超凡朱叶郭迎春刘依于洋郝小可于明
Owner HEBEI UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com