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

Human and vehicle infrared thermal image recognition method based on convolutional neural network

A convolutional neural network and image recognition technology, applied in the field of image recognition, can solve problems such as poor infrared thermal image recognition effect, and achieve the effect of enhancing important features and improving accuracy.

Active Publication Date: 2020-04-21
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF15 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] Aiming at the above-mentioned deficiencies in the prior art, the present invention provides a human and vehicle infrared thermal image recognition method based on a convolutional neural network, which solves the problems of existing image recognition methods based on a convolutional neural network that contain non-living objects and have complex backgrounds. The problem of poor recognition effect of infrared thermal image

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
  • Human and vehicle infrared thermal image recognition method based on convolutional neural network
  • Human and vehicle infrared thermal image recognition method based on convolutional neural network
  • Human and vehicle infrared thermal image recognition method based on convolutional neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0031] The specific embodiments of the present invention are described below so that those skilled in the art can understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.

[0032] Such as figure 1 As shown, a convolutional neural network-based infrared thermal image recognition method for people and vehicles includes the following steps:

[0033] S1. Establish an image data set and divide it into a training set and a test set;

[0034] An infrared thermal imager is used to collect 1000 single-target infrared thermal images including men, women and vehicles, and a data set containing 3000 infr...

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 a human and vehicle infrared thermal image recognition method based on a convolutional neural network. After the training set is augmented, the established infrared thermal image human and vehicle identification network model W-DenseNet is trained; a test set is used for verification to obtain an infrared thermal image human and vehicle identification network model W-DenseNet with high identification degree; the infrared thermal image human and vehicle identification network model W-DenseNet extracts features of different levels of data layer by layer, so that a machineobtains higher level of feature expression and understanding ability, the target category is effectively distinguished, and the purpose of identifying people and vehicles is achieved. A weight parameter learning module is added, so that weight parameters learned in network structure training are weighted on the corresponding convolution layer input feature map, important features are enhanced, invalid features are suppressed, and more effective features are extracted, and therefore, the accuracy of the network model for identifying the gender of men and women in the infrared thermal image canbe improved.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and in particular relates to a method for recognizing infrared thermal images of people and vehicles based on a convolutional neural network. Background technique [0002] The imaging of cameras based on thermal infrared rays is not affected by the light source, especially in low-light conditions such as night and foggy days, and it can still image effectively. Infrared thermal imaging cameras have been widely used in tasks such as intelligent monitoring, disaster search and rescue, and intelligent assisted driving of automobiles. The most common targets in these tasks are people and vehicles, and machine recognition technology for infrared thermal images of people and vehicles plays an important role. Its high accuracy and all-weather characteristics can quickly and accurately identify and record the gender of vehicles and people, assist users to take corresponding actions or measures,...

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): G06K9/62G06K9/00G06N3/04G06N3/08
CPCG06N3/08G06V40/10G06V20/10G06V2201/08G06N3/045G06F18/214G06F18/241
Inventor 骆春波濮希同罗杨张赟疆刘翔许燕徐加朗韦仕才
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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