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

A kind of detection method and application of human biological living body based on subcutaneous blood flow detection

A technology of living body detection and blood flow, applied in the field of biometric identification, can solve the problems of poor user experience, usability and reliability need to be improved, and it is difficult to meet practical application requirements, and achieves the effect of high reliability and low cost.

Active Publication Date: 2017-08-18
TIANJIN UNIV OF SCI & TECH
View PDF10 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, these methods have their own shortcomings. Some require a large number of complex calculations, some require special equipment support, and some methods have poor user experience and are difficult to meet the actual application requirements of various complex occasions. The ease of use and reliability need to be improved.
[0005] Through the search, no patent publications related to the patent application of the present invention have been found

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
  • A kind of detection method and application of human biological living body based on subcutaneous blood flow detection
  • A kind of detection method and application of human biological living body based on subcutaneous blood flow detection
  • A kind of detection method and application of human biological living body based on subcutaneous blood flow detection

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0088] A blood flow-based biometrics living detection method, the steps are as follows:

[0089] (1) Extraction of Classifiable Signals

[0090] First, the position of the sample in the video is determined by using the corresponding method in the original video, such as face detection in complex background. From the video where the sample position has been located, select the skin area corresponding to the sample as the ROI, such as figure 2 shown. In each frame of image, the gray value of the red, green and blue channels of the image is taken, and the video is converted into the corresponding floating-point digital sequence. A fixed-length digital sequence (200 frames) is extracted to form the original signal, as described in formula ①. The original signal is detrended and fluctuated to obtain a classifiable signal. The final classifiable signal has a total of 600 dimensions.

[0091] The specific steps for extracting the classifiable signal above are as follows:

[00...

Embodiment 2

[0133] A method for detecting human biological living body based on subcutaneous blood flow detection, the steps are as follows:

[0134] Change the video sampling frequency in Example 1 to 15fps (15 frames per second), change the number of sample frames to 100, change the input node of the first layer RBM in Example 1 to 100, and use the same network as Example 1 for others The structure and method can achieve the same recognition effect.

Embodiment 3

[0136] A method for detecting human biological living body based on subcutaneous blood flow detection, the steps are as follows:

[0137] Using the same video sampling frequency and detection method as the embodiment, the network structure in the embodiment 1 is changed to 6 layers, and the input and output nodes of each layer are: the first layer of RBM, 200 input nodes, and 5000 output nodes; the second layer of RBM , 5000 input nodes, 2000 output nodes; third-layer RBM, 2000 input nodes, 200 output nodes; fourth-layer RBM, 200 input nodes, 50 output nodes; fifth-layer RBM, 50 input nodes, 10 output nodes; sixth Layer RBM, 10 input nodes, 1 output node. The same identification effect as in Embodiment 1 can also be achieved.

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 a biometric living body detection method based on subcutaneous blood flow. The color video of the skin area under normal light conditions collected by ordinary video acquisition equipment is used as the original signal, and the blood flow signal contained in the original signal is used as the basis for the living body. Use the deep learning neural network composed of RBM to classify and recognize the input signal. The method is based on the biological characteristics of the living body to detect the living body of the sample, and the reliability is high; the method only uses ordinary video acquisition equipment, and these equipment are necessary equipment in the biometric system, without adding additional hardware equipment to the system, and the cost is low. And the algorithm is simple and easy to implement, and can meet the actual requirements of different occasions.

Description

technical field [0001] The invention relates to the technical field of biometric identification, and relates to a method for distinguishing a living body of a human body in biometric identification, in particular to a method for detecting a living body of a human body based on subcutaneous blood flow detection. Background technique [0002] With the development of science and technology and the gradual maturity of some technologies in the field of biometric technology in recent years, biometric (authentication) technology has gradually been widely used. This technology refers to a technology that identifies and discriminates individual identity based on some biological characteristics of the human body, including physiological characteristics and behavioral characteristics. At present, the application of this technology mainly relies on the recognition of physiological characteristics, usually including face recognition, finger (palm) print recognition, iris recognition and ...

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 Patents(China)
IPC IPC(8): G06K9/00G06K9/62G06K9/66
Inventor 刘建征杨巨成熊聪聪陈亚瑞
Owner TIANJIN UNIV OF SCI & 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