Share Email Print
cover

Proceedings Paper

Fast segmentation of tea flowers based on color and region growth
Author(s): Jian Wang; Shuo-Guo Li; Cheng Yang
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

For the development and application of tea flower, the segmentation and counting of tea flower is fast completed by the comprehensive utilization of color and improved region growth algorithm. First, the original RGB color image of tea-leaves is converted into HSI color space, and processed the image enhancement, after the hue H is calculated based on feature hue convergence, the image is converted back to RGB color space; after that the application of improved fast region growth and merging algorithm is applied to select the seeds according to the R, G parameters of tea flower, the region growth is carried to the seed region based on the color similarity and region adjacency, and the region growth and merging are carried out by combining color distance and merging rules. Finally, the segmentation and counting of tea flower is completed. The experimental results show that the algorithm has good connectivity and can be easily and quickly segmented multiple tea flowers from tea-leaves images.

Paper Details

Date Published: 14 August 2019
PDF: 9 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111790R (14 August 2019); doi: 10.1117/12.2539682
Show Author Affiliations
Jian Wang, Sichuan Agricultural Univ. (China)
Shuo-Guo Li, Sichuan Agricultural Univ. (China)
Cheng Yang, Sichuan Agricultural Univ. (China)


Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

© SPIE. Terms of Use
Back to Top
PREMIUM CONTENT
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?
close_icon_gray