An Image Texture Feature Extraction Method Based on Center Window Variation and Four-Quadrant Block Mode

A technology for image texture and feature extraction, applied in character and pattern recognition, instruments, computing, etc., can solve problems that are not conducive to building a fast and robust target detection and tracking system, high computational complexity, etc., and achieve low computational complexity , the effect of strong anti-overfitting ability

Active Publication Date: 2018-11-13
HUAQIAO UNIVERSITY
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For real-time applications, MB-LBP still has high computational complexity, which is not conducive to building a fast and robust target detection and tracking system

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
  • An Image Texture Feature Extraction Method Based on Center Window Variation and Four-Quadrant Block Mode
  • An Image Texture Feature Extraction Method Based on Center Window Variation and Four-Quadrant Block Mode
  • An Image Texture Feature Extraction Method Based on Center Window Variation and Four-Quadrant Block Mode

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0014] Such as figure 1 As shown, a method for extracting image texture feature values ​​of a four-quadrant block mode based on the central window variation of the present invention is to extract image texture features from an image region of 2M×2N (M≥2, N≥2) pixels , through the following steps:

[0015] Step 1. Let the coordinates of the lower left corner of the 2M×2N (M≥2, N≥2) pixel image area be (0,0), and the coordinates of the upper right corner be (2M-1,2N-1); calculate the lower left corner The coordinates are (INT(M / 2), INT(N / 2)), and the coordinates of the upper right corner are (INT(M / 2)+M-1, INT(N / 2)+N-1) central area M× The sum of N pixel values ​​is used as the threshold C; where INT(*) is a rounding operation.

[0016] For example, in figure 1 , M=N=2, the coordinates of the lower left corner of the image area are (0,0), and the coordinates of the upper right corner are (3,3). The central area is the area marked with slashes, the coordinates of the lower le...

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 an image texture feature extraction method based on a four-quadrant block mode of central window variation. For any image area of ​​2M×2N pixels, the sum of M×N pixel values ​​in the central part is firstly calculated as the threshold , and then decompose the image area of ​​2M×2N pixels into 4 sub-regions of M×N pixels, and then calculate the sum of the pixel values ​​of these 4 sub-regions and compare them with the threshold, if the sum of the pixel values ​​is greater than or equal to the threshold, Set the position coding value of the sub-region to 1, otherwise it is 0; finally, multiply the position coding values ​​of the four sub-regions by the corresponding weights and sum them up to obtain the texture feature value of the 2M×2N pixel image region. The invention only needs to use 4 bits to effectively represent the local texture information of the object, and can be applied to target detection, identification and tracking.

Description

technical field [0001] The invention relates to the field of machine vision, in particular to an image texture feature extraction method, which can be applied to target detection, recognition and tracking. Background technique [0002] Target detection, recognition and tracking are hot research topics in the field of pattern recognition. However, due to the existence of interference such as illumination changes, expression changes, occlusions, and complex backgrounds, target detection, recognition and tracking become difficult. In recent years, a large number of object detection, recognition and tracking methods based on texture features have emerged. The accuracy and application effect of these algorithms depend largely on the texture description features used. [0003] Local Binary Pattern (LBP) is a relatively mature texture feature extraction method. The original LBP is defined on a 3×3 pixel block, and the 8-bit LBP code is obtained by calculating the difference betwee...

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): G06K9/46
CPCG06V10/50
Inventor 蔡灿辉葛祖贝曾焕强陈婧
Owner HUAQIAO UNIVERSITY
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