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

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

Abstract

![CDATA[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 = "![CDATA[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 - ![CDATA[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 - ![CDATA[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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