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

Method for recognizing image scale invariant pattern under noise condition

A scale-invariant, pattern recognition technology, applied in the field of detection, recognition of objects of different scales, and image processing, which can solve problems such as sensitivity to background noise, limited detection performance, and unstable influence of correlation peaks.

Inactive Publication Date: 2011-02-16
HARBIN ENG UNIV
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the correlation peaks output by these methods are not stable due to the scale change factor, and are very sensitive to background noise, and the detection performance of these methods is greatly limited.
The radial harmonic filter based on wavelet transform can remove part of the high-frequency noise, but its biggest disadvantage is that the wavelet basis function must be specified in advance, and different basis functions lead to different detection results

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 recognizing image scale invariant pattern under noise condition
  • Method for recognizing image scale invariant pattern under noise condition
  • Method for recognizing image scale invariant pattern under noise condition

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0026] The present invention will be described in more detail below in conjunction with the drawings:

[0027] This method includes two separate stages: (1) training to obtain a correlation filter for a specific object image (reference image); (2) using the obtained correlation filter to recognize the object to be inspected.

[0028] Such as figure 1 , The training phase includes the following steps:

[0029] 1) Use the bidimensional empirical mode decomposition (BEMD) technology to decompose a specific object f(x, y) (usually called a reference image) to obtain the eigenmode function F of each layer of the object i (intrinsicmode functions: IMF) and residual component R;

[0030] f = X i = 1 n ( F i ) + R

[0031] 2) The first layer IMF (high frequency component) F 1 , Perform Merlin radial harmonic decomposition to obtain radial harmonic component;

[0032] f m ( θ ; x 0 , y 0 ) = L - 1 ∫ r 0 R...

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 method for recognizing an image scale invariant pattern under the noise condition. The method comprises two separated stages: a training stage of training the image of a specific object, namely a reference image, to obtain a correlation filter, and a correlation detection stage of recognizing the object to be detected by using the obtained correlation filter. In the method, noise estimation can change adaptively with the change of the signal to noise ratio, and high noise immunity is achieved. The main principle of the method is that: the image can be reconstructed by an intrinsic mode function correlated to the important structure of the image, thus the correlation filter can be built by some specific layers (the intrinsic mode function) to realize the scale invariant pattern recognition; moreover, as the noise distribution on the intrinsic mode function of each layer has a certain rule, the aim of eliminating noise can be fulfilled by the noise distributionrule.

Description

Technical field [0001] The invention relates to an image processing method. In particular, it is a method that uses a computer to detect and recognize objects of different scales in images under noisy conditions. Background technique [0002] One of the main purposes of pattern recognition is to study methods that can perform distortion-invariant recognition (for example, detection methods that are not sensitive to input object distortion). In image processing, three typical object distortions are translation, rotation and scale change. A lot of research has been done on these three kinds of distortions, and some methods have been proposed to obtain distortion invariant detection. Most of these methods are based on the idea of ​​correlation filters. The translation of the object in the image can be easily detected by the Fourier spectrum. If the object in the image rotates in the plane, its Fourier spectrum will also produce corresponding rotation and the period is 2π, so the...

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): G06K9/62
Inventor 尹清波张汝波申丽然李雪耀徐东刘冠群聂东虎
Owner HARBIN ENG UNIV
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