Feature Extraction and Matching for Plant Images

Author

Wang, Peizhen ; Shi, Lei ; Dong, Hengzhi

Author_Institution

Sch. of Electr. Eng. & Inf., Anhui Univ. of Technol., Ma´´an shan, China

Volume

1

fYear

2009

fDate

11-14 Dec. 2009

Firstpage

155

Lastpage

159

Abstract

In this paper, some improvements, including the pyramid frame in image scale space, key point locating method for the SIFT (scale invariant feature transform) algorithm, are developed. In view of the characteristic of plant images, the calculating strategy is also improved. With the improved SIFT algorithm, features in plant images are effectively extracted, and matched with BBF (Best Bin First) algorithm. By matching features extracted from 70 couples of plant images under different illuminate, shadow and focus, the proposed method has been verified to be efficient, and with the improved algorithm the computing time is saved.

Keywords

feature extraction; image matching; Best Bin First algorithm; feature extraction; image scale space; key point locating method; plant image matching; pyramid frame; scale invariant feature transform; Computational intelligence; Computer vision; Feature extraction; Image matching; Image recognition; Information security; Layout; Lighting; Physics; Space technology; feature extraction; matching; plant image; scale invariant feature transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Security, 2009. CIS '09. International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-5411-2

Type

conf

DOI

10.1109/CIS.2009.247

Filename

5376671