Affine invariant recognition of 2D occluded objects using geometric hashing and distance transformation

Albert T. S. Au; Peter W. M. Tsang

doi:10.1109/TENCON.1996.608707

Affine invariant recognition of 2D occluded objects using geometric hashing and distance transformation

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

4 Citations (Scopus)

Abstract

An efficient approach for recognition of partially occluded objects from 2-D grey level images is presented. It can be divided into three stages. The pre-processing stage includes local feature extraction from 2-D grey level images and the formation of hash table. In the recognition stage, geometric hashing technique is used to vote for the point correspondences between the scene and the models. Finally, distance transformation is employed for verification. An average mismatch distance is defined to measure the goodness of the match quantitatively. The approach has been successfully tested on recognizing a number of industrial handtools overlapping each other. © 1996 IEEE

Original language	English
Title of host publication	Proceedings of Digital Processing Applications (TENCON '96)
Publisher	IEEE
Pages	64-67
Volume	1
ISBN (Print)	0-7803-3679-8
DOIs	https://doi.org/10.1109/TENCON.1996.608707
Publication status	Published - Nov 1996
Event	1996 IEEE Region 10 Conference on Digital Signal Processing Applications (TENCON 96) - University of Western Australia, Perth, Australia Duration: 26 Nov 1996 → 29 Nov 1996

Conference

Conference	1996 IEEE Region 10 Conference on Digital Signal Processing Applications (TENCON 96)
Place	Australia
City	Perth
Period	26/11/96 → 29/11/96

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@inproceedings{3d97ae63e16f4ddfbc1bae7200c52e1e,

title = "Affine invariant recognition of 2D occluded objects using geometric hashing and distance transformation",

abstract = "An efficient approach for recognition of partially occluded objects from 2-D grey level images is presented. It can be divided into three stages. The pre-processing stage includes local feature extraction from 2-D grey level images and the formation of hash table. In the recognition stage, geometric hashing technique is used to vote for the point correspondences between the scene and the models. Finally, distance transformation is employed for verification. An average mismatch distance is defined to measure the goodness of the match quantitatively. The approach has been successfully tested on recognizing a number of industrial handtools overlapping each other. {\textcopyright} 1996 IEEE",

author = "Au, {Albert T. S.} and Tsang, {Peter W. M.}",

year = "1996",

month = nov,

doi = "10.1109/TENCON.1996.608707",

language = "English",

isbn = "0-7803-3679-8",

volume = "1",

pages = "64--67",

booktitle = "Proceedings of Digital Processing Applications (TENCON '96)",

publisher = "IEEE",

address = "United States",

note = "1996 IEEE Region 10 Conference on Digital Signal Processing Applications (TENCON 96) ; Conference date: 26-11-1996 Through 29-11-1996",

}

Au, ATS & Tsang, PWM 1996, Affine invariant recognition of 2D occluded objects using geometric hashing and distance transformation. in Proceedings of Digital Processing Applications (TENCON '96). vol. 1, IEEE, pp. 64-67, 1996 IEEE Region 10 Conference on Digital Signal Processing Applications (TENCON 96), Perth, Western Australia, Australia, 26/11/96. https://doi.org/10.1109/TENCON.1996.608707

Affine invariant recognition of 2D occluded objects using geometric hashing and distance transformation. / Au, Albert T. S.; Tsang, Peter W. M.
Proceedings of Digital Processing Applications (TENCON '96). Vol. 1 IEEE, 1996. p. 64-67.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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AU - Au, Albert T. S.

AU - Tsang, Peter W. M.

PY - 1996/11

Y1 - 1996/11

N2 - An efficient approach for recognition of partially occluded objects from 2-D grey level images is presented. It can be divided into three stages. The pre-processing stage includes local feature extraction from 2-D grey level images and the formation of hash table. In the recognition stage, geometric hashing technique is used to vote for the point correspondences between the scene and the models. Finally, distance transformation is employed for verification. An average mismatch distance is defined to measure the goodness of the match quantitatively. The approach has been successfully tested on recognizing a number of industrial handtools overlapping each other. © 1996 IEEE

AB - An efficient approach for recognition of partially occluded objects from 2-D grey level images is presented. It can be divided into three stages. The pre-processing stage includes local feature extraction from 2-D grey level images and the formation of hash table. In the recognition stage, geometric hashing technique is used to vote for the point correspondences between the scene and the models. Finally, distance transformation is employed for verification. An average mismatch distance is defined to measure the goodness of the match quantitatively. The approach has been successfully tested on recognizing a number of industrial handtools overlapping each other. © 1996 IEEE

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DO - 10.1109/TENCON.1996.608707

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 0-7803-3679-8

VL - 1

SP - 64

EP - 67

BT - Proceedings of Digital Processing Applications (TENCON '96)

PB - IEEE

T2 - 1996 IEEE Region 10 Conference on Digital Signal Processing Applications (TENCON 96)

Y2 - 26 November 1996 through 29 November 1996

ER -

Affine invariant recognition of 2D occluded objects using geometric hashing and distance transformation

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