DocumentCode
2193877
Title
Recognition Method of Weed Seeds Based on Computer Vision
Author
Shi Changjiang ; Ji Guangrong
Author_Institution
Dept. of Electron. Eng., Ocean Univ. of China, Qingdao, China
fYear
2009
fDate
17-19 Oct. 2009
Firstpage
1
Lastpage
4
Abstract
In this paper, we provide a method to recognize weed seeds based on computer vision. According to the stability and genetic characteristics described in phytotaxonomy for weed seeds. Image processing method encompasses threshold segmentation and smooth processing etc, nine features parameters are extracted by image processing, which keep RST invariance. The principal components analysis method is adopted to reduce dimensions of weed seeds shape data, the first three principle components as the parameters of the weed seeds shape are put input the BP neural network. The results indicate that the precision ratio of recognition is improved while training time is reduced compared with the traditional simple method. This method can be well applied in weed seeds recognition.
Keywords
backpropagation; image segmentation; neural nets; object recognition; principal component analysis; BP neural network; Image processing method; RST invariance; computer vision; features parameters extracted; phytotaxonomy; principal components analysis method; recognition method; smooth processing; threshold segmentation; weed seeds; Computer vision; Data mining; Feature extraction; Genetics; Image processing; Image segmentation; Neural networks; Principal component analysis; Shape; Stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location
Tianjin
Print_ISBN
978-1-4244-4129-7
Electronic_ISBN
978-1-4244-4131-0
Type
conf
DOI
10.1109/CISP.2009.5305507
Filename
5305507
Link To Document