Image tampering blind forensics method based on detection-segmentation architecture

A blind forensics, image technology, applied in image enhancement, neural architecture, image analysis and other directions, can solve the problems of solidification of detection methods, inaccurate positioning of tampered areas, etc., and achieve the effect of improving detection recall rate and

Pending Publication Date: 2021-10-29
上海舜瞳科技有限公司
View PDF0 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to propose a blind image tampering forensics algorithm based on detection-segmentation architecture for the pr

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 tampering blind forensics method based on detection-segmentation architecture
  • Image tampering blind forensics method based on detection-segmentation architecture
  • Image tampering blind forensics method based on detection-segmentation architecture

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0031] Next, the technical solutions in the embodiments of the present invention will be described in connection with the drawings in the embodiments of the present invention, and the described embodiments are merely embodiments of the present invention, not all of the embodiments. The embodiments described with reference to the accompanying drawings are exemplary, and is intended to be construed as limiting the invention.

[0032] like figure 1 As shown, it is the basic flow of the algorithm of the present invention, and the specific steps are as follows:

[0033] like figure 1 As shown, an image-based image tampering method method based on the detection-segmentation architecture, the specific steps are as follows:

[0034] Step 1: Graphical data pretreatment, the data image of the present embodiment uses CASIA2 and Columbia public split data sets of 5303 images, and the label software Labelme marks its tampering area MASK. The original image and Mask image size are fixed to 1024...

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 tampering blind forensics method based on a detection-segmentation framework, and belongs to the field of deep learning and computer vision. According to the method, the tampering detection problem of an image is solved from the perspective of semantic segmentation, and tampering region detection and region segmentation are carried out by adopting an improved Mask R-CNN network. In a data preprocessing stage, original pictures are subjected to data enhancement, and sample richness is enhanced. In a feature extraction stage, a path from bottom to top is newly added to achieve fusion of multi-level feature information, and sufficient context semantic information is further obtained. In an RPN training stage, Focal Loss is adopted to solve the problem of imbalance between positive and negative samples, so that the network is easier to converge. In a post-processing stage, a Soft-NMS algorithm is adopted to solve the problems of false detection and missing detection caused by overlapping detection frames, and the detection recall rate is improved. According to the method, blind forensics of various tampered (mode) images in a complex scene is realized, and the detection and positioning precision of a tampered area is effectively improved.

Description

Technical field [0001] The present invention relates to the field of digital image forensics, computer vision, and digital image processing, and is specifically a method of authenticity and integrity detection of digital images without any prior information. Background technique [0002] Digital image blind tailor technology is directly delivered to the image content in the field of digital image forensics. With the development of computer technology and information technology, the image is getting more and more popular, and the tampering content is getting more and more, the tampering means is increasing, causing the difficulty of challenge the image to the image. Therefore, it is necessary to study the strong blind test algorithm, which can accurately perform authenticity and integrity detection of tampering images. [0003] Traditional image tampering blind drawback method is mainly a truly detection of image of the "handmade design feature + classifier". Such methods solve if...

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): G06T7/00G06T7/11G06K9/62G06N3/04
CPCG06T7/0002G06T7/11G06T2207/20016G06T2207/20081G06T2207/20084G06T2207/10004G06N3/045G06F18/213G06F18/253G06F18/214
Inventor 周大可张志伟吴子涵
Owner 上海舜瞳科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap