Abnormity determining method for low-resolution infrared image

An infrared image and abnormal situation technology, applied in the direction of instruments, character and pattern recognition, computer parts, etc., can solve the problem of inaccurate image judgment, and achieve high judgment accuracy, low false alarm rate, and low computational complexity. Effect

Inactive Publication Date: 2017-07-04
成都智锗科技有限公司
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The object of the present invention is: when judging the low-resolution passive far-infrared image above, the feature extraction method adopted during high-resolution infrared image processing is not suitable for low-resolution infrared image feature extraction, resulting in inaccurate image judgment problem, the present invention proposes a low-resolution infrared image sleep abnormality judgment method

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
  • Abnormity determining method for low-resolution infrared image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] All the features disclosed in this specification, except mutually exclusive features and / or steps, can be combined in any way.

[0028] Combine below figure 1 The present invention will be described in detail.

[0029] Any feature disclosed in this specification (including any appended claims, abstract and drawings), unless expressly stated otherwise, may be replaced by alternative features which are equivalent or serve a similar purpose. That is, unless expressly stated otherwise, each feature is one example only of a series of equivalent or similar features.

[0030] In the present invention, at first the system is trained, and the training steps include:

[0031] Step 1: Perform image label classification on N sleep passive far-infrared images with a resolution of m×n, and perform image preprocessing on the N sleep passive far-infrared images after label classification. The preprocessing process includes image interpolation, smoothing, and normalization. Any exist...

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 sleep abnormity determining method for a low-resolution infrared image. The method belongs to the technical field of artificial intelligence. The method comprises the steps of determining expression of an abnormity of a sleep image in a low-resolution passive far-infrared condition by means of the artificial intelligence, firstly performing targeted preprocessing and characteristic generation on a low-resolution passive far-infrared image of which the kind is marked, training a classifying system, obtaining an appropriate characteristic selecting and extracting method and a classifier method; performing targeted preprocessing and characteristic generation on the low-resolution passive far-infrared image to be determined intelligently, performing classification by means of the selected characteristic selecting and extracting method and the trained classifying system, and obtaining the abnormity output of the low-resolution passive far-infrared image to be determined intelligently. The sleep abnormity determining method for the low-resolution infrared image has advantages of relatively high robustness and relatively low operation complexity in determining the sleep abnormity of the low-resolution passive far-infrared images of different sleep individuals on the condition that a false alarm rate is ensured.

Description

technical field [0001] The invention relates to the technical fields of image processing and artificial intelligence, in particular to a method for judging abnormal sleep conditions of low-resolution infrared images. Background technique [0002] At present, with the increasing development and maturity of image processing and acquisition technology, a large number of applications of artificial intelligence in image processing have emerged in people's daily life. Passive far infrared has the characteristics of clear imaging in the dark, zero radiation, non-contact, and good privacy, and has been widely used. However, due to the high cost of far infrared collection technology, the resolution of low-cost collection equipment for ordinary households is very low. How to use low-resolution passive far-infrared images to judge intelligent abnormal situations is of great significance. On the one hand, this technology can be used to form high-cost-effective, clear imaging in the dar...

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): G06K9/00G06K9/62
CPCG06V20/00G06F18/24
Inventor 王帅段昶罗钦文
Owner 成都智锗科技有限公司
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