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

Space Pyramid Object Recognition Method Based on Kernel Function Matching

A space pyramid, object recognition technology, applied in character and pattern recognition, instruments, calculations, etc., can solve problems such as increasing the difficulty of object recognition, achieve good recognition results, improve representativeness, and improve accuracy.

Active Publication Date: 2018-11-16
JIANGNAN UNIV
View PDF6 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, the differences between similar objects further exacerbate the difficulty of object recognition

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
  • Space Pyramid Object Recognition Method Based on Kernel Function Matching
  • Space Pyramid Object Recognition Method Based on Kernel Function Matching
  • Space Pyramid Object Recognition Method Based on Kernel Function Matching

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0026] In order to better illustrate the purpose, concrete steps and characteristics of the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings:

[0027] refer to figure 1 , a kind of space pyramid object recognition method based on kernel function matching that the present invention proposes, mainly comprises the following steps:

[0028] Step 1. Collect sample images of objects to be identified, and divide the collected sample image data into training samples and test samples;

[0029] Step 2: Convert the images of the training samples and test samples into grayscale images, and convert the data type of the grayscale images into double-precision floating point types; then scale the size of the image so that its height and width are in [50,200 ]between;

[0030] Step 3, extracting ED-SIFT (Efficient Dense Scale-invariant Feature Transform) descriptors of training samples and test samples;

[0031]...

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 patent of the present invention discloses a space pyramid object recognition method based on kernel function matching. It includes the following steps: extracting the ED-SIFT (Efficient Dense Scale-invariant Feature Transform) descriptor of the object image; using the k-means++ clustering algorithm to cluster the ED-SIFT descriptor of the training sample to obtain a visual dictionary; introducing a spatial pyramid, The visual word histogram of the training sample and the test sample is obtained by using the kernel function matching; the training of the training sample and the identification of the test sample are completed by using the SVM classifier. The algorithm proposed in this patent has a high degree of recognition for object image recognition, and in the case of few training samples, a simple SVM classifier can obtain a good classification effect.

Description

Technical field: [0001] The invention relates to the field of machine vision, in particular to a space pyramid object recognition method based on kernel function matching. Background technique: [0002] With the rapid development of computer and multimedia technology, the scale of digital images and videos has expanded rapidly. Although massive image data facilitates people's life, it also brings great troubles to people's life. How to quickly and accurately find images of objects of interest to us from massive image data is becoming more and more difficult. Therefore, how to fully and accurately understand images, how to organize image data in an orderly, efficient and reasonable manner, and retrieve the required images has gradually become one of the hotspots in computer vision research. [0003] In recent years, the object recognition algorithm with Bag of Words (BoW) as the key technology has made the most outstanding progress. In recent decades, experts and scholars ...

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 Patents(China)
IPC IPC(8): G06K9/62G06K9/52
CPCG06V10/42G06V10/758G06F18/23213
Inventor 孔军张迎午蒋敏高坤柳晨华
Owner JIANGNAN 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