Method for extracting and describing DAISY-based feature with mirror face turning invariance

A feature extraction and feature point technology, applied in the field of image processing, can solve problems such as failure of DAISY extraction method

Inactive Publication Date: 2010-01-20
TIANJIN UNIV
View PDF0 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0010] The purpose of the present invention is to overcome the above-mentioned deficiencies of the prior art, and provide a method that can solve the problem of failure of feature

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 extracting and describing DAISY-based feature with mirror face turning invariance
  • Method for extracting and describing DAISY-based feature with mirror face turning invariance
  • Method for extracting and describing DAISY-based feature with mirror face turning invariance

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0030] Since DAISY itself is a description method for image depth map estimation and 3D reconstruction, and does not consider the robustness in scale space, DAISY itself is flawed. Aiming at this defect, the present invention adopts the method of Hessian-Gaussian feature detection to improve it.

[0031] First, the scale of the input image is changed. This change is done through Gaussian convolution. In a series of images of different scales, the extreme point of the gray value of the pixel is found for each pixel. However, not all extreme points meet the criteria as feature points. Since the feature points need to have certain prominence and robustness, by setting appropriate thresholds for Difference of Gaussian and Hessian matrix , so as to filter the candidate points with low contrast and edge response of feature points respectively. The extreme points left after these two steps of screening are the desired feature points. For these extreme points, after fitting them with...

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 belongs to the technical field of image processing, relating to a method for extracting and describing DAISY-based features with mirror face turning invariance. The method comprises the following steps: (1) carrying out Gaussian kernel convolution processing on an input image; (2) continually carrying out Gauss difference processing on the image to detect the extreme points thereof; (3) screening feature points; (4) precisely positioning the positions of feature points; (5) determining the direction parameter of each feature point; (6) summing gradient module values on both sides respectively using the main direction as a dividing line; and (7) organizing the pixel units in a Gaussian weight window to carry out encoding and normalized operations, thereby generating description data of the image. The invention enhances the robustness of the feature extraction and description method to mirror imaging problem, and expands application fields of computer vision.

Description

technical field [0001] The invention belongs to the technical field of image processing and relates to an image feature extraction method. Background technique [0002] Today's computer technology is developing rapidly, and the application fields of computer vision and image retrieval are becoming more and more extensive, which also highlights their importance. Popular 3D reconstruction, object recognition, camera calibration, robot binocular navigation, etc. are all based on computer vision, so reasonably and effectively solving the problems existing in computer vision or improving imperfections can give the computer industry even A huge boost from the scientific community. Computer vision is based on the idea that the computer can simulate human (mammalian) vision to achieve a certain degree of intelligence. Together with image retrieval, it is necessary to extract and analyze the features of the image, so the definition and extraction scheme of image features has a pivo...

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 操晓春郭晓杰刘晗宇李靖徐庆
Owner TIANJIN UNIV
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