Rotating stomata detection based on anchor-free networks

Bo Wang; Chaoyang Liu; Fan Zhang

doi:10.1117/12.3006161

10 October 2023 Rotating stomata detection based on anchor-free networks

Bo Wang, Chaoyang Liu, Fan Zhang

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127994N (2023) https://doi.org/10.1117/12.3006161
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Stomata play a crucial role in the photosynthetic process of plants by regulating the water and carbon dioxide levels in their leaves. The effective identification of stomata in plant leaves has become a hot topic in related research fields. With the development of deep learning, some automatic stomatal identification methods have been proposed in the past. However, these methods are based on horizontal anchor network, which can be challenging when collecting stomatal images on plant leaves since most stomata are rotated. As a result, the proposed methods cannot completely identify rotated stomata, leading to reduced efficiency in subsequent stomatal trait analysis. To address this issue, we propose an improved method for the automatic identification of rotating stomata in maize leaves based on the CenterNet (Objects as Points) detection model. The network structure of CenterNet is enhanced by adding an angle prediction branch, which enables the detection of rotating stomata. Experimental results show that the improved CenterNet deep learning model achieves a recognition precision of 94.3% on the maize leaf stomata dataset. This method can automate the identification of maize leaf stomata, assisting researchers in conducting large-scale studies on stomatal morphology and structure.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Bo Wang, Chaoyang Liu, and Fan Zhang "Rotating stomata detection based on anchor-free networks", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127994N (10 October 2023); https://doi.org/10.1117/12.3006161

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
4 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Deep learning

Education and training

Process modeling

Polishing

Simulation of CCA and DLA aggregates

Image processing

Image segmentation

Show All Keywords

Keywords/Phrases

Search In:

Publication Years