Research & Development World

  • R&D World Home
  • Topics
    • Aerospace
    • Automotive
    • Biotech
    • Careers
    • Chemistry
    • Environment
    • Energy
    • Life Science
    • Material Science
    • R&D Management
    • Physics
  • Technology
    • 3D Printing
    • A.I./Robotics
    • Software
    • Battery Technology
    • Controlled Environments
      • Cleanrooms
      • Graphene
      • Lasers
      • Regulations/Standards
      • Sensors
    • Imaging
    • Nanotechnology
    • Scientific Computing
      • Big Data
      • HPC/Supercomputing
      • Informatics
      • Security
    • Semiconductors
  • R&D Market Pulse
  • R&D 100
    • Call for Nominations: The 2025 R&D 100 Awards
    • R&D 100 Awards Event
    • R&D 100 Submissions
    • Winner Archive
    • Explore the 2024 R&D 100 award winners and finalists
  • Resources
    • Research Reports
    • Digital Issues
    • R&D Index
    • Subscribe
    • Video
    • Webinars
  • Global Funding Forecast
  • Top Labs
  • Advertise
  • SUBSCRIBE

Computer Vision: Computers Perceive Image Curves like Artists

By R&D Editors | November 23, 2015

Interest curves perceived by a computerImagine computers being able to understand paintings or paint abstract images much like humans. Bo Li demonstrates a breakthrough concept in the field of computer vision using curves and lines to represent image shapes and furthermore to recognize objects. He defends his dissertation on November 27, 2015, at Umeå University.

Human perception can recognize objects through image features, such as shapes and curves. For example, we can identify faces, animals, cars, and other daily objects in simple sketch images. For computers, however, recognizing objects or image features are challenging tasks.

Accurate modeling of image features is very important in a wide range of computer vision applications, for example: image registration, 3-D reconstruction and object detection. In future technologies, such as Google Car, virtual reality or AI brain, image features will remain fundamental components. In spite of the fact that hundreds of solutions for the detection of image features already exist, up until now there had been a solid concept missing.

In his doctoral dissertation at the Department of Applied Physics and Electronics, Bo Li has developed a breakthrough concept in computer vision: interest curves.

“With this method, the computer can redraw an image using curve strokes and recognize objects through these curves,” says Bo Li.

The concept brings about brand new dimensions of understanding image features including points, regions, lines and curves. It also enables these features to be represented within the same theoretical framework. It advances the standard for future research regarding image features, as it provides practical guidance to the field at the same time.

According to Bo Li, the most important element in feature extraction is the robustness. His results show that his method enables curves and lines to be detected robustly under various image transformations and disturbances.

In the past, curves and lines have not been as popular as points and regions in the field of computer vision because they lack enough robustness and Li’s new theory and algorithms will change this.

“Curves and lines are naturally more useful than points, because humans use these shapes to describe the world,” explains Bo Li.

His doctorate work shows many advantages of using curve features in computer vision applications.

The dissertation has been published digitally

Related Articles Read More >

From solar system simulations to SaaS savings, how Codeium’s AI agent empowers non-coders and scientists alike
Aardvark AI forecasts rival supercomputer simulations while using over 99.9% less compute
Quantum Brilliance, Pawsey integrate room-temp quantum with HPC on NVIDIA GH200
Frontier supercomputer reveals new detail in nuclear structure
rd newsletter
EXPAND YOUR KNOWLEDGE AND STAY CONNECTED
Get the latest info on technologies, trends, and strategies in Research & Development.
RD 25 Power Index

R&D World Digital Issues

Fall 2024 issue

Browse the most current issue of R&D World and back issues in an easy to use high quality format. Clip, share and download with the leading R&D magazine today.

Research & Development World
  • Subscribe to R&D World Magazine
  • Enews Sign Up
  • Contact Us
  • About Us
  • Drug Discovery & Development
  • Pharmaceutical Processing
  • Global Funding Forecast

Copyright © 2025 WTWH Media LLC. All Rights Reserved. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of WTWH Media
Privacy Policy | Advertising | About Us

Search R&D World

  • R&D World Home
  • Topics
    • Aerospace
    • Automotive
    • Biotech
    • Careers
    • Chemistry
    • Environment
    • Energy
    • Life Science
    • Material Science
    • R&D Management
    • Physics
  • Technology
    • 3D Printing
    • A.I./Robotics
    • Software
    • Battery Technology
    • Controlled Environments
      • Cleanrooms
      • Graphene
      • Lasers
      • Regulations/Standards
      • Sensors
    • Imaging
    • Nanotechnology
    • Scientific Computing
      • Big Data
      • HPC/Supercomputing
      • Informatics
      • Security
    • Semiconductors
  • R&D Market Pulse
  • R&D 100
    • Call for Nominations: The 2025 R&D 100 Awards
    • R&D 100 Awards Event
    • R&D 100 Submissions
    • Winner Archive
    • Explore the 2024 R&D 100 award winners and finalists
  • Resources
    • Research Reports
    • Digital Issues
    • R&D Index
    • Subscribe
    • Video
    • Webinars
  • Global Funding Forecast
  • Top Labs
  • Advertise
  • SUBSCRIBE