Supercharge Your Innovation With Domain-Expert AI Agents!

Method for identifying dollar denominations through facial recognition

A technology of face recognition and denomination, which is applied in the field of face recognition and identification of dollar denominations. It can solve the problems that the identification accuracy cannot meet the requirements, the denomination size cannot be recognized, and the noise resistance is poor. It achieves wide practicability, strong noise resistance, and distinguishes high degree of effect

Inactive Publication Date: 2014-06-25
HUAZHONG UNIV OF SCI & TECH
View PDF0 Cites 14 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The disadvantages of the existing technology are: poor resistance to noise; when the characteristic area is slightly polluted, the identification is very likely to be wrong, the denomination cannot be identified, and the identification accuracy cannot meet the requirements

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
  • Method for identifying dollar denominations through facial recognition
  • Method for identifying dollar denominations through facial recognition
  • Method for identifying dollar denominations through facial recognition

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0038] The present invention will be further described below through specific embodiments.

[0039] Take a number of dollar banknotes of various denominations, get their grayscale images, correct and normalize them to a uniform size, and dig out a fixed portrait area; for each point in the portrait area, calculate the differential excitation in its eight neighbors, each Pixels can get an angle whose value is between (-π / 2,π / 2], quantize it into 100 equal divisions, and quantize (θ-π / 200,θ+π / 200] into θ, For example, (-π / 200, π / 200] is quantized to 0, (-π / 200, 3π / 200] is quantized to 2π / 200; then the statistical angle histogram is regarded as a 100-dimensional vector; from the above In the first step, the Weber local descriptor WLD eigenvector is trained, and an optimal eigenvector is selected for each denomination of dollars as the standard eigenvector of this denomination; for each dollar with a recognized denomination, its eigenvector is extracted; The obtained eigenvectors...

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 relates to dollar identification technologies, in particular to a method for identifying dollar denominations through facial recognition. An existing technology for identifying dollar denominations has the defects that noise resistance is poor, and identification is likely to go wrong when feature regions are slightly contaminated. The method comprises the steps that dollar bills with various denominations are selected, gray level images of the dollar bills are obtained and then are corrected and normalized to be of a uniform size; with regard to all points in facial regions, differential excitation is calculated in the eight neighborhoods of the points, each pixel point obtains an angle with the value ranging within (-pi / 2, pi / 2], each angle is quantized into100 aliquots, and (theta-pi / 200, theta+pi / 200] is quantized into theta; statistics is performed on angle histograms to obtain a multi-dimensional vector a; standard samples of various denominations are trained, and the optimal feature vector is selected; the obtained feature vector is compared with a standard vector. The method for identifying the dollar denominations through the facial recognition has the advantages that no artificial participation is needed for looking for features in the recognition process, the degree of distinction is high, transportability is good, and a machine can have quick recognition ability through the method.

Description

technical field [0001] The invention relates to a dollar identification technology, in particular to a method for face recognition and identification of dollar denominations. Background technique [0002] With the development of economic globalization, the circulation of various currencies has increased, and the circulation of US dollars in the world has also continued to increase. In order to seek personal benefits, lawbreakers around the world manufacture various versions of counterfeit US dollars, endangering financial security. Since the US dollars of various denominations have the same paper size, and the US dollars of different denominations are relatively similar in color, the size of the US dollar denomination cannot be determined by the size or color of the paper. The existing technology uses the method of identifying the characteristics of a small area to identify the dollar denomination: find a small area, analyze its characteristics, such as the number in the lo...

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): G06K9/00G07D7/20G07D7/202
Inventor 张巍巍尤新革付祥旭李方震李山雨
Owner HUAZHONG UNIV OF SCI & TECH
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com