A Method of Fruits Recognition Based on SIFT Characteristics Matching

Author

Song Wan-gan ; Guo Hong-Xia ; Wang Yan

Author_Institution

Sch. of Comput. Sci. & Technol., Huaibei Coal Ind. Teachers´ Coll., Huaibei, China

Volume

3

fYear

2009

fDate

7-8 Nov. 2009

Firstpage

119

Lastpage

122

Abstract

SIFT (scale invariant feature transform) used in fruits recognition presents a characteristics matching algorithm according to fruits images. The algorithm uses SIFT characteristics as matching feature, then introduces Euclidean distance as the similarity metrics of image matching, and uses a method of setting a threshold value to delete the false matching points. The experimental results prove that the algorithm can effectively solve the problem of fruits recognition and matching with translation, rotation, scaling, and partial occlusion.

Keywords

image matching; object recognition; transforms; Euclidean distance; SIFT characteristics matching algorithm; feature extraction; fruits recognition; image matching; matching feature; scale invariant feature transform; similarity metrics; Character recognition; Educational institutions; Feature extraction; Image matching; Image processing; Image recognition; Image registration; Lighting; Machine vision; Noise robustness; Feature Extraction; Feature Matching; Scale Invariant Feature Transform; Work-piece Recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-3835-8

Electronic_ISBN

978-0-7695-3816-7

Type

conf

DOI

10.1109/AICI.2009.484

Filename

5376555