A novel virus infection clustering for flower images identification

Siu Yeung Cho; Peh Ti Lim

doi:10.1109/ICPR.2006.144

A novel virus infection clustering for flower images identification

Siu Yeung Cho
, Peh Ti Lim

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

16 Citations (Scopus)

Abstract

Computer-aided flower identification is a very useful tool for plant species identification aspect. In this paper, a study was made on a development of content based image retrieval system to characterize flower images efficiently. In this system, a novel Virus Infection Clustering is proposed to cluster the image database to improve the searching efficiency. Experimental results show that the developed system can yield promising results for flower image retrieval.

Original language	English
Title of host publication	Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006
Pages	1038-1041
Number of pages	4
DOIs	https://doi.org/10.1109/ICPR.2006.144
Publication status	Published - 2006
Externally published	Yes
Event	18th International Conference on Pattern Recognition, ICPR 2006 - Hong Kong, China Duration: 20 Aug 2006 → 24 Aug 2006

Publication series

Name	Proceedings - International Conference on Pattern Recognition
Volume	2
ISSN (Print)	1051-4651

Conference

Conference	18th International Conference on Pattern Recognition, ICPR 2006
Country/Territory	China
City	Hong Kong
Period	20/08/06 → 24/08/06

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 15 Life on Land

ASJC Scopus subject areas

Computer Vision and Pattern Recognition

Access to Document

10.1109/ICPR.2006.144

Cite this

@inproceedings{252c32c376a8446ebbe4b97b6d40b0c8,

title = "A novel virus infection clustering for flower images identification",

abstract = "Computer-aided flower identification is a very useful tool for plant species identification aspect. In this paper, a study was made on a development of content based image retrieval system to characterize flower images efficiently. In this system, a novel Virus Infection Clustering is proposed to cluster the image database to improve the searching efficiency. Experimental results show that the developed system can yield promising results for flower image retrieval.",

author = "Cho, \{Siu Yeung\} and Lim, \{Peh Ti\}",

year = "2006",

doi = "10.1109/ICPR.2006.144",

language = "English",

isbn = "0769525210",

series = "Proceedings - International Conference on Pattern Recognition",

pages = "1038--1041",

booktitle = "Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006",

}

Cho, SY & Lim, PT 2006, A novel virus infection clustering for flower images identification. in Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006., 1699385, Proceedings - International Conference on Pattern Recognition, vol. 2, pp. 1038-1041, 18th International Conference on Pattern Recognition, ICPR 2006, Hong Kong, China, 20/08/06. https://doi.org/10.1109/ICPR.2006.144

A novel virus infection clustering for flower images identification. / Cho, Siu Yeung; Lim, Peh Ti.
Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006. 2006. p. 1038-1041 1699385 (Proceedings - International Conference on Pattern Recognition; Vol. 2).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A novel virus infection clustering for flower images identification

AU - Cho, Siu Yeung

AU - Lim, Peh Ti

PY - 2006

Y1 - 2006

N2 - Computer-aided flower identification is a very useful tool for plant species identification aspect. In this paper, a study was made on a development of content based image retrieval system to characterize flower images efficiently. In this system, a novel Virus Infection Clustering is proposed to cluster the image database to improve the searching efficiency. Experimental results show that the developed system can yield promising results for flower image retrieval.

AB - Computer-aided flower identification is a very useful tool for plant species identification aspect. In this paper, a study was made on a development of content based image retrieval system to characterize flower images efficiently. In this system, a novel Virus Infection Clustering is proposed to cluster the image database to improve the searching efficiency. Experimental results show that the developed system can yield promising results for flower image retrieval.

UR - https://www.scopus.com/pages/publications/34047239251

U2 - 10.1109/ICPR.2006.144

DO - 10.1109/ICPR.2006.144

M3 - Conference contribution

AN - SCOPUS:34047239251

SN - 0769525210

SN - 9780769525211

T3 - Proceedings - International Conference on Pattern Recognition

SP - 1038

EP - 1041

BT - Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006

T2 - 18th International Conference on Pattern Recognition, ICPR 2006

Y2 - 20 August 2006 through 24 August 2006

ER -

A novel virus infection clustering for flower images identification

Abstract

Publication series

Conference

UN SDGs

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this