Title :
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
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;
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
DOI :
10.1109/AICI.2009.415
