Method for constructing compact image local feature descriptor

A local feature and construction method technology, applied in the field of visual processing, can solve the problems of high cost of feature matching calculations, affecting the discrimination and intuition of image local feature descriptors, achieving fast matching speed, reducing generation time and matching time, The effect of low dimensionality

Active Publication Date: 2014-07-30
HEFEI UNIV OF TECH
View PDF4 Cites 20 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the defects that the high dimensionality of image local descriptors with strong descriptive ability leads to high cost of feature matching calculation, and the dim

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 constructing compact image local feature descriptor
  • Method for constructing compact image local feature descriptor
  • Method for constructing compact image local feature descriptor

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0050] In order to have a further understanding and understanding of the structural features of the present invention and the achieved effects, the preferred embodiments and accompanying drawings are used for a detailed description, as follows:

[0051] like figure 1 As shown, a method for constructing a compact image local feature descriptor described in the present invention comprises the following steps:

[0052] The first step is to determine the feature area, determine the position of the feature area through feature point detection, and select an appropriate scale and size for the feature area. The step of determining the characteristic area can be done according to the method in the prior art, select the appropriate scale and area size, for example, the scale is selected as 1.6, and the size is 41×41 pixels, and a feature area R is determined. Here, according to different applications, the scale and The size of the feature region can be changed.

[0053] (1) Use the a...

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 relates to a method for constructing a compact image local feature descriptor. Compared with the prior art, the defects that an image local descriptor with high descriptive power is high in dimensionality, so that feature matching computing cost is large, and a common dimensionality reduction method influences the distinction degree and visuality of the image local feature descriptor are overcome. The method comprises the following steps that a feature region is determined; the feature region is partitioned and numbered; codes of leading central symmetry local binary patterns of points are worked out in the feature region; in units of partitioned sub-regions, a feature vector of the leading central symmetry local binary pattern of each partitioned sub-region is worked out; according to the sequence of the numbers of the partitioned sub-regions, the feature vectors of the leading central symmetry local binary patterns of all the partitioned sub-regions are arranged. The descriptor constructed with the method has the advantages of being low in dimensionality and high in descriptive power and distinction degree, high robustness of rotation transformation and illumination transformation of images is achieved, calculation is easy, and the matching speed is high.

Description

technical field [0001] The invention relates to the technical field of visual processing, in particular to a method for constructing a compact image local feature descriptor. Background technique [0002] In recent years, the local features of images have attracted the attention of many researchers. Because of their robustness to image deformation and light transformation and robustness to partial occlusion of images, they are widely used in vision applications, such as object retrieval, object recognition, etc. , face recognition, behavior classification, etc. The ideal local feature descriptor requires good description ability and discrimination, and can be quickly generated and matched. The low-dimensional characteristics of local descriptors are an important factor to ensure their fast matching, but many influential local feature descriptors have high dimensions. For the same local feature descriptor, reducing its dimension may reduce its corresponding degree of discrim...

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
IPC IPC(8): G06K9/46G06T7/00
Inventor 檀结庆李莹莹钟金琴
Owner HEFEI UNIV OF TECH
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