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

Image blind detection method based on secondary seam clipping features

A seam cropping and blind detection technology, applied in the field of image blind detection based on secondary seam cropping features, can solve problems such as insufficient detection rate and high computational complexity.

Active Publication Date: 2015-05-06
TIANJIN POLYTECHNIC UNIV
View PDF2 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0019] However, the detection rate of existing methods is still insufficient and can be further improved. At the same time, the feature dimensions extracted by existing methods are relatively high, which requires high computational complexity.

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 blind detection method based on secondary seam clipping features
  • Image blind detection method based on secondary seam clipping features
  • Image blind detection method based on secondary seam clipping features

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0066] Below in conjunction with accompanying drawing, the present invention is described in further detail:

[0067] The present invention proposes a new seam cutting detection method through the feature of additional seam cutting behavior. The present invention is based on the fact that although the seam cropping operation can maintain the main content of the image, it still causes some distortion and deformation; if the number of seams to be deleted exceeds a certain range, the main information of the original image will be lost. is corrupted so that the cropped image is no longer similar to the original image.

[0068] Based on the observation after performing an additional seam cropping operation on the image, it is found that the similarity, energy ratio and seam distance difference of the original image are very different from the seam cropped image. This invention proposes a new image blindness The detection method is mainly used to detect whether the image has underg...

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 provides an image blind detection method based on secondary seam clipping features and belongs to the field of blind image forensics image processing. The method includes: (1) conducting additional seam clipping operation on an image to obtain an additional seam clipping image; (2) conducting feature extraction which includes calculating the similarity feature, the energy ratio feature and the stitch distance difference feature between the image and the corresponding additional seam clipping image; (3) detecting seam clipping through a training support vector machine by utilizing the similarity feature, the energy ratio feature and the stitch distance difference feature which are extracted. The method is low in feature dimension, has lower calculation complexity and meanwhile has higher detection rate.

Description

technical field [0001] The invention belongs to the field of image blind evidence collection in image processing, and in particular relates to an image blind detection method based on secondary seam cutting features. Background technique [0002] Seam carving, that is, seam cutting, is an effective method for resizing images based on content awareness. It has now gained some popularity due to its ability to overcome the limitations of traditional scaling and cropping. Seam cropping automatically removes the least important path in the image to reduce the size of the image, this least important path is called a seam, and can also insert seams to enlarge the image. A seam is defined as an 8-connected low-energy pixel line running through the image from top to bottom or left to right. Dynamic programming techniques can be used to select the optimal seam in each direction, and the so-called optimal seam refers to the seam with the smallest accumulated energy, where the accumul...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/62
Inventor 柯永振山青青闵卫东郭景
Owner TIANJIN POLYTECHNIC UNIV
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