Automatic identification method for anti-counterfeit labels based on ciphertext domain

An anti-counterfeiting label and automatic identification technology, applied in character and pattern recognition, secure communication through chaotic signals, encryption device with shift register/memory, etc., can solve the problems of less research on automatic identification algorithms of anti-counterfeiting labels, and achieve strong The effect of anti-conventional attack ability, broad market prospect and high practical value

Inactive Publication Date: 2018-02-02
HAINAN UNIVERSITY
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, there are few researches on the automatic identification algorithm of anti-counterfeiting labels based on ciphertext field

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
  • Automatic identification method for anti-counterfeit labels based on ciphertext domain
  • Automatic identification method for anti-counterfeit labels based on ciphertext domain
  • Automatic identification method for anti-counterfeit labels based on ciphertext domain

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0090] Below in conjunction with accompanying drawing, the present invention will be further described, and the simulation platform of use is Matlab2010a, selects a product anti-counterfeit label as original anti-counterfeit image ( figure 1 ), expressed as F(i,j), where 1≤i≤220, 1≤j≤76, and then encrypt it ( figure 2 ), expressed as E(i,j), and the corresponding DCT coefficient matrix is ​​FD(i,j), where 1≤i≤220; 1≤j≤76. Considering the robustness, we take 32 coefficients, and get the feature vector according to the coefficients. After detecting V'(i,j) through the anti-counterfeiting algorithm, we can judge the authenticity of the product by calculating the normalized correlation coefficient NC (Normalized Cross Correlation).

[0091] Randomly select 100 sets of independent binary sequences with a sequence length of 32 bits (the value is +1 or -1), and then arbitrarily remove one of them from the data (here we choose the 50th group) as the embedded feature vector.

[0092...

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 automatic identification technology for anti-counterfeit labels based on a ciphertext domain, and belongs to the field of multimedia signal processing. The automatic identification method comprises the steps of firstly encrypting the anti-counterfeit labels in a frequency domain by using DFT (Discrete Fourier Transform) and Logistic Mapping; then performing DCT (DiscreteCosine Transform) on the encrypted images, extracting feature vectors of the encrypted images to build a feature vector library; and encrypting the anti-counterfeiting labels to be tested, extractingfeature vectors of the encrypted anti-counterfeiting labels in a DCT domain, and then identifying the encrypted anti-counterfeiting labels through calculating the similarity between the feature vectors. Disclosed by the invention is an automatic identification technology for the encrypted anti-counterfeiting labels based on the DFT ciphertext domain, which has good ability of resisting conventional attacks and geometric attacks.

Description

technical field [0001] The invention belongs to the field of multimedia signal processing, and relates to an image feature recognition based on DFT encryption, chaotic map (LogisticMap) and DCT, in particular to an automatic recognition method of anti-counterfeiting labels based on cipher text domain, and belongs to the field of anti-counterfeiting technology. technical background [0002] Now with the vigorous development of social economy, there are many fake and shoddy goods on the market, which violate the rights and interests of producers and consumers, so some effective anti-counterfeiting methods are needed. Today's anti-counterfeiting technologies are various, but they also have their shortcomings. For example, sneaking into the laser-type plastic film anti-counterfeiting label, because this technology is a traditional anti-counterfeiting technology, it appeared earlier, and the imitation technology tends to be mature and perfect, and it can no longer play a good role...

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): G06Q30/00G06K9/52G06K9/62H04L9/00H04L9/06
CPCH04L9/001H04L9/0618G06Q30/0185G06T2207/20052G06V10/52G06V10/757
Inventor 李京兵马伟生王兆晖沈重
Owner HAINAN UNIVERSITY
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