Content-based structural recognition for flower image classification

Author

Cho, Siu-Yeung

Author_Institution

Div. of Eng., Univ. of Nottingham Ningbo China, Ningbo, China

fYear

2012

fDate

18-20 July 2012

Firstpage

541

Lastpage

546

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

botany; content-based retrieval; image classification; image recognition; image retrieval; probability; computer-aided flower identification; content based image retrieval system; content-based structural recognition; flower image classification; flower image retrieval; plant species identification aspect; probabilistic based recursive model; structural pattern recognition; Feature extraction; Image color analysis; Image segmentation; Merging; Neural networks; Probabilistic logic; Shape; image classification; neural network; structural recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications (ICIEA), 2012 7th IEEE Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4577-2118-2

Type

conf

DOI

10.1109/ICIEA.2012.6360787

Filename

6360787