Fast segmentation of tea flowers based on color and region growth

Jian Wang; Shuo-Guo Li; Cheng Yang

doi:10.1117/12.2539682

14 August 2019 Fast segmentation of tea flowers based on color and region growth

Jian Wang, Shuo-Guo Li, Cheng Yang

Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 111790R (2019) https://doi.org/10.1117/12.2539682
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China

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.

Citation Download Citation

Jian Wang, Shuo-Guo Li, and Cheng Yang "Fast segmentation of tea flowers based on color and region growth", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111790R (14 August 2019); https://doi.org/10.1117/12.2539682

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available