Content-based structural recognition for flower image classification

Siu Yeung Cho

doi:10.1109/ICIEA.2012.6360787

Content-based structural recognition for flower image classification

Siu Yeung Cho^*

^*Corresponding author for this work

Department of Electrical and Electronic Engineering

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

11 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 method of structural pattern recognition based on probabilistic based recursive model is proposed to classify flower images. Experimental results show that the developed system can yield promising results for flower image retrieval.

Original language	English
Title of host publication	Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012
Pages	541-546
Number of pages	6
DOIs	https://doi.org/10.1109/ICIEA.2012.6360787
Publication status	Published - 2012
Event	2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012 - Singapore, Singapore Duration: 18 Jul 2012 → 20 Jul 2012

Publication series

Name	Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012

Conference

Conference	2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012
Country/Territory	Singapore
City	Singapore
Period	18/07/12 → 20/07/12

UN SDGs

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

SDG 15 Life on Land

Free Keywords

image classification
neural network
structural recognition

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/ICIEA.2012.6360787

Cite this

@inproceedings{40f12c3911b848288ed24cac13067b5a,

title = "Content-based structural recognition for flower image classification",

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 method of structural pattern recognition based on probabilistic based recursive model is proposed to classify flower images. Experimental results show that the developed system can yield promising results for flower image retrieval.",

keywords = "image classification, neural network, structural recognition",

author = "Cho, \{Siu Yeung\}",

note = "Copyright: Copyright 2013 Elsevier B.V., All rights reserved.; 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012 ; Conference date: 18-07-2012 Through 20-07-2012",

year = "2012",

doi = "10.1109/ICIEA.2012.6360787",

language = "English",

isbn = "9781457721175",

series = "Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012",

pages = "541--546",

booktitle = "Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012",

}

Cho, SY 2012, Content-based structural recognition for flower image classification. in Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012., 6360787, Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012, pp. 541-546, 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012, Singapore, Singapore, 18/07/12. https://doi.org/10.1109/ICIEA.2012.6360787

Content-based structural recognition for flower image classification. / Cho, Siu Yeung.
Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012. 2012. p. 541-546 6360787 (Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012).

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

TY - GEN

T1 - Content-based structural recognition for flower image classification

AU - Cho, Siu Yeung

PY - 2012

Y1 - 2012

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 method of structural pattern recognition based on probabilistic based recursive model is proposed to classify flower images. 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 method of structural pattern recognition based on probabilistic based recursive model is proposed to classify flower images. Experimental results show that the developed system can yield promising results for flower image retrieval.

KW - image classification

KW - neural network

KW - structural recognition

UR - https://www.scopus.com/pages/publications/84871682776

U2 - 10.1109/ICIEA.2012.6360787

DO - 10.1109/ICIEA.2012.6360787

M3 - Conference contribution

AN - SCOPUS:84871682776

SN - 9781457721175

T3 - Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012

SP - 541

EP - 546

BT - Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012

T2 - 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012

Y2 - 18 July 2012 through 20 July 2012

ER -

Content-based structural recognition for flower image classification

Abstract

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Conference

UN SDGs

Free Keywords

ASJC Scopus subject areas

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