Mr. Samuel De Paula Profile

Samuel De Paula

at Univ. de São Paulo

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 4 October 2023 Open Access

Weed detection among soybean plants in artificial lighting environment using multispectral images and computer vision

Yuri Sarreta Oda, Lucas Orlandi de Oliveira, Samuel De Paula, André Orlandi de Oliveira, Jarbas Caiado de Castro Neto

Proceedings Volume 12746, 1274608 (2023) https://doi.org/10.1117/12.2686194

KEYWORDS: Cameras, RGB color model, Infrared imaging, Light sources and illumination, Multispectral imaging, Infrared radiation, Computer vision technology, Agriculture, Infrared cameras, Near infrared

Read Abstract +

Precision Agriculture stands out as one of the most promising areas for the development of new technologies around the world. Some advances from this area include the mapping of productivity areas and the development of sensors for climate and soil analysis, improving the smart use of resources during crop management and helping farmers during the decision-making stages. Among the problems of modern agriculture, the intensive and non-localized use of herbicides causes environmental issues, contributes to elevated costs in farmers’ budgets and results in applications of chemical substances in non-target organisms. Although there are many selective herbicide spraying systems available for use, the majority working principle is based upon chlorophyll detectors, thus not being able to distinguish crop plants from weeds with high accuracy in crop’s post-emergence herbicide applications (“green-on-green” application). The main objective of this study is to develop a multispectral camera system for in-crop weed recognition using Computer Vision techniques. The system was built with four monochromatic CMOS sensor cameras with monochromatic wavelength bandpass filters (green, red, near infrared and infrared) and a RGB camera. Soybean and weed plants images were captured in a controlled environment using an automated v-slot rail system to simulate the movement of a spray tractor in the field. Infrared images presented higher precision (90.5%) and recall (89.3%) values compared to the other monochromatic bands, followed by RGB (87.0% and 86.1%, respectively) and near infrared images (83.6% and 87.9%), suggesting that infrared wavelengths plays an important role in plant detection and classification. Our results state that the combination of Computer Vision and multispectral images of plants is a more efficient approach for targeting weeds among crop plants for post-emergence herbicide applications.

DOWNLOAD PAPER

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

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:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years