Multi-chessboards localisation based on FCM and Radon transform algorithm

Authors:
Dong-/Sheng Zhou;Xiao-/Yong Fang
Affiliations:
Key Laboratory of Advanced Design and Intelligent Computing (/Dalian University)/, Ministry of Education, Dalian 116622, China/ School of Mechanical Engineering, Dalian University of Technol ...;School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China
Venue:
International Journal of Computer Applications in Technology
Year:
2010

Citing 6
Cited 0

A Flexible New Technique for Camera Calibration

IEEE Transactions on Pattern Analysis and Machine Intelligence
Empirical evaluation of a calibration chart detector

Machine Vision and Applications
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing

Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Visual Marker Detection and Decoding in AR Systems: A Comparative Study

ISMAR '02 Proceedings of the 1st International Symposium on Mixed and Augmented Reality
Marker Tracking and HMD Calibration for a Video-Based Augmented Reality Conferencing System

IWAR '99 Proceedings of the 2nd IEEE and ACM International Workshop on Augmented Reality
A new shape descriptor defined on the Radon transform

Computer Vision and Image Understanding

Quantified Score

Hi-index	0.00

Visualization

Abstract

Owing to the simple and striking structure, chessboard is widely used as the camera calibration pattern. Locating the chessboard in an image is a prerequisite step during the calibration procedure, especially under the situation that there exists more than one chessboard with random relative positions in an image. A robust recognition method based on Fuzzy C-Means (FCM) clustering and Radon Transform (RT) algorithm is presented to solve the problem above. Experiments show that the method is effective to locate and distinguish the chessboards with a large and complicated background from each other. The proposed method also provides a possibility to calibrate a camera with one shot.