A fast image analysis technique for the line tracking robots

Authors:
Krzysztof Okarma;Piotr Lech
Affiliations:
West Pomeranian University of Technology, Szczecin, Faculty of Electrical Engineering, Signal Processing and Multimedia Engineering, Szczecin, Poland;West Pomeranian University of Technology, Szczecin, Faculty of Electrical Engineering, Signal Processing and Multimedia Engineering, Szczecin, Poland
Venue:
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
Year:
2010

Citing 6
Cited 0

Simulation and the Monte Carlo Method

Simulation and the Monte Carlo Method
Evolving a Vision-Based Line-Following Robot Controller

CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
Computational methods for complex stochastic systems: a review of some alternatives to MCMC

Statistics and Computing
Monte Carlo Based Algorithm for Fast Preliminary Video Analysis

ICCS '08 Proceedings of the 8th international conference on Computational Science, Part I
A Statistical Reduced-Reference Approach to Digital Image Quality Assessment

ICCVG 2008 Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers
Video scene segmentation using Markov chain Monte Carlo

IEEE Transactions on Multimedia

Quantified Score

Hi-index	0.00

Visualization

Abstract

Fast and simplified image processing and analysis methods can be successfully implemented for the robot control algorithms. Statistical methods seem to be very useful for such an approach, mainly because a significant reduction of analysed data is possible. In the paper the use of the fast image analysis based on the Monte Carlo area estimation for the simplified binary representation of the image is analysed and proposed for the mobile robot control. A possible implementation of the proposed method can applied in the line tracking robots and such application has been treated as the basic one for the testing purposes.