Title :
Study on Image Recognition of Insect Pest of Sugarcane Cotton Aphis Based on Rough Set and Fuzzy C-means Clustering
Author :
Zhao, Jinhui ; Liu, Muhua ; Yao, Mingyin
Author_Institution :
Coll. of Eng., Jiangxi Agric. Univ., Nanchang, China
Abstract :
Sugarcane cotton aphis is a common insect pest in China. Rough set and fuzzy C-means clustering were applied to identify the insect pest of sugarcane cotton aphis. Rough set was used to obtain the characteristic parameters of identify insect pest of sugarcane cotton aphis. Then, fuzzy C-means clustering was used to extract the regions of the insect pest of sugarcane cotton aphis. The experimental results showed that 17 images were segmented correctly and the accurate rate of the segmentation was 85%.
Keywords :
cotton; fuzzy set theory; image recognition; image segmentation; pest control; rough set theory; fuzzy C means clustering; identify insect pest; image recognition; image segmentation; rough set; sugarcane cotton aphis based; Cotton; Diseases; Educational institutions; Fuzzy sets; Fuzzy systems; Image recognition; Image segmentation; Information technology; Insects; Machine vision; fuzzy C-means clustering; image recognition; rough set; sugarcane cotton aphis;
Conference_Titel :
Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
Conference_Location :
Nanchang
Print_ISBN :
978-0-7695-3859-4
DOI :
10.1109/IITA.2009.295
