Adaptive circular object detection

Christopher N. Young; Ju Jia Zou

doi:10.1109/ICSPCS.2008.4813677

Adaptive circular object detection

Christopher N. Young
, Ju Jia Zou

School of Engineering, Design & Built Environment

Research output: Chapter in Book / Conference Paper › Conference Paper

4 Citations (Scopus)

Abstract

In this paper a robust and adaptive method of circular object detection is proposed. The proposed method aims to limit the need for parameter adjustment when applied to a wide range of different images, by implementing a hybrid algorithm using the Circular Hough Transform for region segmentation, and a refined localised version of the Randomized Circle Detection algorithm to perform circular object detection. As a result the overall speed and accuracy are improved when compared to other circle detection algorithms.

Original language	English
Title of host publication	Proceedings of the 2nd International Conference on Signal Processing and Communication Systems, held on Gold Coast, Qld., 15-17 December, 2008
Publisher	Queensland University of Technology
Number of pages	6
ISBN (Print)	9780975693469
DOIs	https://doi.org/10.1109/ICSPCS.2008.4813677
Publication status	Published - 2008
Event	International Conference on Signal Processing and Communication Systems - Duration: 16 Dec 2013 → …

Conference

Conference	International Conference on Signal Processing and Communication Systems
Period	16/12/13 → …

Keywords

Hough transform
algorithms
circle detection algorithms
image processing
pattern recognition systems

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10.1109/ICSPCS.2008.4813677

Cite this

@inproceedings{802efb56a87949e4b7819b4ee19c31be,

title = "Adaptive circular object detection",

abstract = "In this paper a robust and adaptive method of circular object detection is proposed. The proposed method aims to limit the need for parameter adjustment when applied to a wide range of different images, by implementing a hybrid algorithm using the Circular Hough Transform for region segmentation, and a refined localised version of the Randomized Circle Detection algorithm to perform circular object detection. As a result the overall speed and accuracy are improved when compared to other circle detection algorithms.",

keywords = "Hough transform, algorithms, circle detection algorithms, image processing, pattern recognition systems",

author = "Young, \{Christopher N.\} and Zou, \{Ju Jia\}",

year = "2008",

doi = "10.1109/ICSPCS.2008.4813677",

language = "English",

isbn = "9780975693469",

booktitle = "Proceedings of the 2nd International Conference on Signal Processing and Communication Systems, held on Gold Coast, Qld., 15-17 December, 2008",

publisher = "Queensland University of Technology",

note = "International Conference on Signal Processing and Communication Systems ; Conference date: 16-12-2013",

}

Young, CN & Zou, JJ 2008, Adaptive circular object detection. in Proceedings of the 2nd International Conference on Signal Processing and Communication Systems, held on Gold Coast, Qld., 15-17 December, 2008. Queensland University of Technology, International Conference on Signal Processing and Communication Systems, 16/12/13. https://doi.org/10.1109/ICSPCS.2008.4813677

TY - GEN

T1 - Adaptive circular object detection

AU - Young, Christopher N.

AU - Zou, Ju Jia

PY - 2008

Y1 - 2008

N2 - In this paper a robust and adaptive method of circular object detection is proposed. The proposed method aims to limit the need for parameter adjustment when applied to a wide range of different images, by implementing a hybrid algorithm using the Circular Hough Transform for region segmentation, and a refined localised version of the Randomized Circle Detection algorithm to perform circular object detection. As a result the overall speed and accuracy are improved when compared to other circle detection algorithms.

AB - In this paper a robust and adaptive method of circular object detection is proposed. The proposed method aims to limit the need for parameter adjustment when applied to a wide range of different images, by implementing a hybrid algorithm using the Circular Hough Transform for region segmentation, and a refined localised version of the Randomized Circle Detection algorithm to perform circular object detection. As a result the overall speed and accuracy are improved when compared to other circle detection algorithms.

KW - Hough transform

KW - algorithms

KW - circle detection algorithms

KW - image processing

KW - pattern recognition systems

UR - http://handle.uws.edu.au:8081/1959.7/45177

U2 - 10.1109/ICSPCS.2008.4813677

DO - 10.1109/ICSPCS.2008.4813677

M3 - Conference Paper

SN - 9780975693469

BT - Proceedings of the 2nd International Conference on Signal Processing and Communication Systems, held on Gold Coast, Qld., 15-17 December, 2008

PB - Queensland University of Technology

T2 - International Conference on Signal Processing and Communication Systems

Y2 - 16 December 2013

ER -

Adaptive circular object detection

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