Driver eye state monitoring method based on invariant moment

An eye state and driver technology, applied in the fields of instruments, character and pattern recognition, computer parts, etc., can solve the problems of large amount of calculation of high-order moments and not meeting real-time requirements.

Inactive Publication Date: 2014-09-17
NANJING GENERAL ELECTRONICS
View PDF2 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] If the 7th-order central moment of the human eye image is used alone as a feature for recognition, it is necessary to match the entire human eye image, especially the calculation of the high-order moments is very large, which does not meet the real-time 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
  • Driver eye state monitoring method based on invariant moment
  • Driver eye state monitoring method based on invariant moment
  • Driver eye state monitoring method based on invariant moment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0040] The present invention monitors the principle of driver's eye state as follows:

[0041] The simple human eye state monitoring method is more suitable for the front of the face and is sensitive to noise. It cannot perform efficient and stable eye state monitoring under various conditions such as complex backgrounds, lighting, expressions, and head changes. Moment invariant is a highly condensed image feature, which is invariant to multiple distortions such as translation, grayscale, scale, and rotation, and is robust to noise. If the 7th-order central moment of the human eye image is used alone as a feature for recognition, it is necessary to match the entire human eye image, especially the calculation of the high-order moment is very large, which does not meet the real-time requirements. The present invention combines the advantages of the central mom...

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 driver eye state monitoring method based on invariant moment. After an facial image is preprocessed, an eye area is extracted out according to an image threshold segmentation method based on the two-dimension digital image fractional order integral and the Legendre moment, first three orders of central moments and four feature quantities of the eye area are combined to serve as a feature vector for matching recognition of eye states, Euclidean distances between feature vectors of an area to be detected and feature vectors of a template image are calculated one by one, and thus the eye state of a driver is judged out. The respective advantages of the central moments and the feature quantities of the eye area are combined, the number of features for matching recognition is decreased, and space dimensionality of the features is reduced; by introducing the Euclidean distances between the feature vectors of the candidate eye area and the feature vectors of the eye template image, algorithm complexity is further lowered, and the system recognition speed is increased.

Description

【Technical field】 [0001] The invention relates to the technical field of human eye detection, in particular to a method for monitoring the driver's eye state based on invariant moments. 【Background technique】 [0002] With the development of economy and transportation, various vehicles are increasing day by day, and traffic accidents are also increasing, which has become a very serious social problem, and fatigue driving is an important factor leading to traffic accidents. Therefore, reducing traffic accidents caused by driving fatigue has become a research hotspot, and everyone wants to work hard to develop a system that can monitor the driver's alertness level in real time and provide early warning to the driver in any unsafe state. [0003] Studies have shown that eye status has a high correlation with driver fatigue and can reliably reflect fatigue status, and eye positioning is a prerequisite for judging eye status. At present, there are mainly learning-based, template...

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): G06K9/00G06K9/46
Inventor 陈杰
Owner NANJING GENERAL ELECTRONICS
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