Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Thin-Layer Chromatography (TLC): Overview01:11

Thin-Layer Chromatography (TLC): Overview

1.3K
Thin-layer chromatography (TLC) is a chromatography technique that separates compounds based on their polarity. TLC typically uses polar silica gel, a form of silicon dioxide, as the stationary phase. The silica gel contains hydroxyl (OH) groups on its surface, which form hydrogen bonds with polar compounds, influencing their adhesion to the stationary phase.
To begin the analysis, a mixture of compounds is spotted on the starting line on the TLC plate using a thin capillary. The bottom of the...
1.3K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Tumor cell intrinsic and extrinsic features predict prognosis in estrogen receptor positive breast cancer.

PLoS computational biology·2022
Same author

Comparison of the diagnostic efficacy of <sup>68</sup> Ga-FAPI-04 PET/MR and <sup>18</sup>F-FDG PET/CT in patients with pancreatic cancer.

European journal of nuclear medicine and molecular imaging·2022
Same author

Addressing Extreme Propensity Scores in Estimating Counterfactual Survival Functions via the Overlap Weights.

American journal of epidemiology·2022
Same author

68 Ga-FAPI-04 Versus 18 F-FDG PET/CT in a Case of Peutz-Jeghers Syndrome.

Clinical nuclear medicine·2022
Same author

Fatty acid synthase (Fasn) inhibits the expression levels of immune response genes via alteration of alternative splicing in islet cells.

Journal of diabetes and its complications·2022
Same author

Risk Factors and Outcome Variables of Cardiorenal Syndrome Type 1 in Acute Myocardial Infarction Patients.

International journal of general medicine·2022
Same journal

Therapeutic potential of crude protein extracts from two Egyptian freshwater snails Lanistes carinatus and Bellamya unicolor.

Scientific reports·2026
Same journal

Microbial contamination of donor corneas and post-keratoplasty endophthalmitis: a comparison between Japanese and U.S. eye banks using cold storage.

Scientific reports·2026
Same journal

Prevalence and contributing factors of virological non-suppression among adult patients on first-line antiretroviral therapy in tertiary hospitals in Ethiopia.

Scientific reports·2026
Same journal

An in vitro comparison of color stability between alkasite and different restorative materials in various staining solutions.

Scientific reports·2026
Same journal

Toward accessible mRNA LNP formulation: systematic evaluation of mixing strategies and key parameters.

Scientific reports·2026
Same journal

A network analysis of personality traits, mentalizing, and psychological health in Chinese college students.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: Jun 8, 2025

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus
05:57

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Published on: April 8, 2019

6.8K

An algorithm for lane detection based on RIME optimization and optimal threshold.

Shuang Zhai1, Xiao Zhao1, Guoming Zu1

  • 1College of Computer Science and Engineering, Changchun University of Technology, Changchun, 130012, China.

Scientific Reports
|November 8, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a new lane detection algorithm for challenging road conditions, improving accuracy to 93.87% by integrating frost/ice optimization and optimal thresholding for safer autonomous driving.

Keywords:
Image segmentationLane line detectionRIME optimization algorithm

More Related Videos

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
11:41

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

20.3K
Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques
10:53

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques

Published on: March 12, 2019

7.0K

Related Experiment Videos

Last Updated: Jun 8, 2025

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus
05:57

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Published on: April 8, 2019

6.8K
Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
11:41

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

20.3K
Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques
10:53

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques

Published on: March 12, 2019

7.0K

Area of Science:

  • Computer Vision
  • Autonomous Driving Systems
  • Image Processing

Background:

  • Complex road conditions like frost and ice significantly degrade lane line detection performance.
  • Existing algorithms struggle with low visibility and interference, impacting autonomous vehicle safety.

Purpose of the Study:

  • To develop a robust lane line detection algorithm resilient to adverse weather and road conditions.
  • To enhance the accuracy and efficiency of lane detection for autonomous driving systems.

Main Methods:

  • A novel algorithm integrating frost/ice optimization with optimal thresholding.
  • Pre-processing using Retinex theory for noise reduction and detail preservation.
  • Segmentation via enhanced OTSU thresholding with tent mapping.
  • Bird's-eye view transformation and adaptive sliding window for feature identification.
  • Lane line fitting using RANSAC with a parabolic model.

Main Results:

  • Achieved a lane line detection accuracy rate of 93.87%, outperforming traditional Hough Transform (43.2%) and combined methods (89.16%).
  • Demonstrated significant advantages in threshold calculation error and computational efficiency compared to similar image segmentation algorithms.
  • Exhibited remarkable robustness against interference factors in complex road conditions.

Conclusions:

  • The proposed algorithm effectively addresses challenges in low lane line detection rates caused by complex road conditions.
  • The method offers superior accuracy and robustness, crucial for reliable autonomous driving systems.
  • Publicly available code facilitates further research and development in intelligent transportation systems.