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
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;
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
DOI :
10.1109/CISP.2009.5305507