Mr. Cary McCraine Profile

Cary McCraine

at Mississippi State University

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 | 14 May 2019 Presentation + Paper

Plant density estimation and weeds mapping on row crops at emergence using low altitude UAS imagery

C. Daniel McCraine, Sathishkumar Samiappan, Joby Prince Czarnecki, Darrin Dodds

Proceedings Volume 11008, 110080Y (2019) https://doi.org/10.1117/12.2520252

KEYWORDS: Algorithm development, Image analysis, Near infrared, Reflectivity, Sensors, Hough transforms, Binary data, Image processing, Vegetation, Cameras

Read Abstract +

Plant density estimation during the emergence phase is critical for early-season decision making. Estimation of both crop and weed density is critical for addressing early season issues. Mapping of weeds in crops at any stage can be useful; however, early competition from weeds is frequently most detrimental to yield. The objectives of this study were to develop a set of algorithms that accurately estimated the crop and weed density at emergence from sUAS imagery, and to do so using methods which were operationally feasible on production-field scale. The areas of interest were Mississippi cotton fields, where weeds were present. The imagery was collected using the standard integrated camera on a DJI Phantom 4 Pro quadcopter. A Hough transform-based approach for density estimation of crop and weed was used. The detection process began by extracting all plants from the soil background based on visible atmospherically resistant index values, and further discriminated between crop and weed using Hough line transform, followed by connected component analysis. The algorithm development utilized five subsets of image data collected, where overall accuracy was 83%. The algorithm was applied to a different production cotton field in the following year. Overall accuracy remained the same; however, commission error was reduced. The addition of near infrared reflectance could improve accuracies as many errors were due to a lack of “greenness” in plants, which is the primary factor in assigning visible atmospherically resistant index values.

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