Title :
Multispectral image segmentation of rice seedlings in paddy fields by fuzzy c-means clustering
Author :
Qi, Long ; Ma, Xu ; Zuo, Yanjun ; Liao, Xinglong ; Guo, Hongjiang
Author_Institution :
Key Lab. of Key Technol. on Agric. Machine & Equip., South China Agric. Univ., Guangzhou, China
Abstract :
The objective of this research was to develop a method for segmenting rice seedlings from background in a multispectral image of paddy field. Multispectral images of paddy field were taken by a high resolution multispectral camera. The DVI (Difference vegetation index) image which could reduce the image noises was suitable for seedlings recognition by analyzing spectral characteristics of the objects in near infrared, red, and green wavebands. The difference vegetation index was calculated by subtracting a red image from a near infrared image and the segmentation threshold was confirmed based on fuzzy C clustering arithmetic. 212 images were acquired to do validated test and 210 images got satisfied segmentation results. The accuracy of image segmentation was above 99%.
Keywords :
agriculture; fuzzy set theory; image denoising; image segmentation; pattern clustering; difference vegetation index; fuzzy C-means clustering; green waveband; high resolution multispectral camera; image noises; multispectral image segmentation; near infrared image; paddy fields; red waveband; rice seedlings; segmentation threshold; Agriculture; Cameras; Image segmentation; Indexes; Pixel; Reflectivity; Vegetation mapping; difference vegetation index; fuzzy c-means clustering; image segmentation; rice seedling;
Conference_Titel :
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6513-2
DOI :
10.1109/CISP.2010.5646677
