SURF-Based Multi-scale Resolution Histogram for Insect Recognition

Author

Huang Shi-Guo ; Li Xiao-lin ; Zhou Ming-quan ; Geng Guo-hua

Author_Institution

Comput. & Inf. Coll., Fujian Agric. & Forestry Univ., Fuzhou, China

Volume

2

fYear

2009

fDate

7-8 Nov. 2009

Firstpage

445

Lastpage

448

Abstract

Automatic insect recognition are time-saving and labor-saving and global feature extraction algorithms have been used for recognition. However, local features based automatic insect recognition is not studied. Therefore, in our research, SURF algorithm is used to extract local features of insect images and then the features are taken as input of multi-scale histogram algorithm. The experimental results show that the accurate recognition rate of SURF based multi-scale histogram method is 89%.

Keywords

biology computing; feature extraction; image recognition; image resolution; SURF-based multiscale resolution histogram; automatic insect recognition; global feature extraction; insect images; local features; multiscale histogram; Artificial intelligence; Computational intelligence; Educational institutions; Feature extraction; Histograms; Image databases; Image recognition; Insects; Object recognition; Spatial databases; SURF; insect recognition; multi-scale histogram;

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.2009.415

Filename

5375848