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

A Fast Recognition Method of Connected Domain Labels in Binary Images

A connected domain labeling and recognition method technology, applied in the field of fast recognition of binary image connected domain labeling, can solve the problems of unsuitability for parallelization, low efficiency, and lack of real-time processing conditions for large images, and achieves a simple method and improves scanning efficiency. , the effect of improving the overall performance of the system

Active Publication Date: 2017-03-01
LIUZHOU VOCATIONAL & TECHN COLLEGE
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is to provide a fast recognition method of connected domain marks in binary images to solve the shortcomings of the prior art, such as low efficiency, unsuitability for parallelization, and lack of real-time processing conditions for large images

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
  • A Fast Recognition Method of Connected Domain Labels in Binary Images
  • A Fast Recognition Method of Connected Domain Labels in Binary Images
  • A Fast Recognition Method of Connected Domain Labels in Binary Images

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0039] A method for quickly identifying connected domain markers in a binary image, the method comprising the following steps:

[0040] S1. Initialization of CPU and GPU:

[0041] Utilize the server environment to set up a virtual graphics workstation cluster, the virtual graphics workstation 1 constitutes a dynamic virtual machine through logical combination, and the server environment includes a server cluster 2 and a main control server 3 (see figure 2 ), the server computer or server cluster is equipped with multiple CUDA-based GPU graphics cards, and each GPU graphics card is connected through an SLI interface (abbreviation for Scalable Link Interface, which is an upgradeable connection interface in Chinese), and the blocks of the CUDA-based platform The size is 256 or 512; the server computer or server cluster is used as a computing node, and the master control server is responsible for scheduling and controlling all tasks, and is responsible for managing the computing...

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 a quick recognizing method of a binary image connected domain label, and relates to an image recognizing method used for crack recognizing, remote sensing image path extracting, remote sensing image shape target recognizing and the like. The quick recognizing method of the binary image connected domain label comprises the steps that S1 a CPU and a GPU are initialized; S2 an image is scanned; S3 scanned results are stored in a disk of a server environment; S4 merging processing is conducted on the scanned results; S5 whether the scanning is iteration scanning or not is judged, if yes, the step S6 is executed and otherwise the step S1 is repeated; S6 processing results are stored and the method ends. The quick recognizing method of the binary image connected domain label can improve the overall performance of a system and is applicable to real-time processing of large images, the scanning efficiency is high, and the method is simple and convenient and fast to implement.

Description

technical field [0001] The invention relates to an image recognition (target extraction) method for crack identification, remote sensing image path extraction and shape target recognition, in particular to a fast identification method for binary image connected domain marks. Background technique [0002] A binary image refers to an image in which each pixel is either black or white, and its gray value has no intermediate transition. The advantage is that it takes up less space. The disadvantage is that when representing images of people and landscapes, binary images can only describe their outlines and cannot describe details. The traditional connected domain labeling methods are: [0003] 1. Connected point-by-point scanning method, this method needs to deal with a large number of repeated marks, the logic is complex, and the efficiency is low. [0004] 2. Seed filling method, which is more efficient, but not suitable for parallelization. [0005] The above two types of...

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): G06F9/38
Inventor 王慧余剑韦小波陆晓希盘承军张德平
Owner LIUZHOU VOCATIONAL & TECHN COLLEGE
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