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

Image characteristics extraction method based on global and local structure amalgamation

A technology of image feature extraction and local structure, applied in computer parts, character and pattern recognition, instruments, etc., can solve problems such as image recognition methods that have not yet been found

Inactive Publication Date: 2009-02-18
DONGHUA UNIV
View PDF5 Cites 26 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

No image recognition method that combines these two features has been found in further searches

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
  • Image characteristics extraction method based on global and local structure amalgamation
  • Image characteristics extraction method based on global and local structure amalgamation
  • Image characteristics extraction method based on global and local structure amalgamation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0045] The present invention is specifically described below in conjunction with embodiment:

[0046] Satimage database experiment

[0047] Satimage is one of the data sets provided by UCI for machine learning research. It contains 6 types of data, and the number of attribute features of samples is 36. This experiment uses 2400 data points in Satimage, 400 for each type, and training samples The number is 180, and the number of test samples is 2220. figure 1 As the overall framework of the experimental method, the preprocessing in the framework is mainly to normalize the data, and normalize the model of the data to between 0 and 1. Such as figure 1 Shown, the present invention can be divided into the following steps:

[0048] Step 1. Construct a weighted adjacency graph of the training data

[0049] Among the 400 data points of each of the 6 types of data, the first 30 data are selected to form the training database, and the remaining data are used to form the test databas...

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

Provided is an image feature extraction method based on global and local structure fusion, characterized by comprising: 1) constructing a weight adjacent map; 2) determining laplacian matrix of similar matrix, degree matrix and images, 3) determining scatter matrix inside the kind and between the kind; 4) determining projection matrix, 5) identifying. The invention provides a feature extraction method of fusing the global structure information and the local structure information, wherein complex features fused of the global feature and the local feature are extracted, thereby the method has strong resolving power. The method not only has the characteristics of holding the reflection method locally, namely holding the characteristics of manifold structure of data; moreover has the characteristics of linear discrimination analysis method, namely assembling the date of the kind more compact to enlarge the distance between the kinds. The invention is applied in image recognition, thereby increasing identifying performance.

Description

technical field [0001] The invention relates to an image feature extraction method based on fusion of global and local structures, belonging to the field of intelligent information processing. Background technique [0002] Image recognition technology has become one of the hotspots in research and application today. This technology has been successfully applied in face recognition, license plate recognition, video surveillance, target tracking and recognition and other fields. [0003] As one of the key links of image recognition, the feature extraction method is to map the original high-dimensional image data to a low-dimensional feature space. This technology has become a research hotspot in the field of machine learning and pattern recognition. Commonly used feature extraction methods include Linear Discriminant Analysis (LDA for short), Locality Preserving Projection (LPP for short), etc. [0004] The linear discriminant analysis method is a classic algorithm in patte...

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): G06K9/62G06K9/46
CPCG06K9/6252G06K9/6234G06V10/7715G06F18/2132G06F18/21375
Inventor 孙韶媛谷小婧方建安
Owner DONGHUA 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