Detection and Counting of Tassels for Maize Crop Monitoring using Multispectral Images

Kumar, A. and Rajalakshmi, P. and Desai, U.B. and et al, . (2020) Detection and Counting of Tassels for Maize Crop Monitoring using Multispectral Images. In: 2020 IEEE International Conference on Computing, Power and Communication Technologies, GUCON 2020, 2 October 2020 - 4 October 2020.

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Abstract

Crop monitoring is essential to increase its production and to fulfill future food-demand. For maize crops, the tassels' detection is imperative as tassels give knowledge about its pollination, reproduction stages, and yield. In general, the health and growth stages of a crop are monitored with manual vision, which is time-consuming and labor-intensive. Therefore, Unmanned Aerial Vehicle (UAV) is the main focus of research using different sensors for automating crop-health and growth monitoring processes. However, the identification of objects like tassels is challenging due to the size and number of objects, backgrounds, illuminations, and occlusions of objects in images acquired in UAV based remote sensing. This manuscript proposed a novel method to detect tassels of maize crops using UAV based remote sensing. The proposed method used images of five bands: Red, Blue, Green, Rededge, and Near-InfraRed (NIR). The performance analysis demonstrated that the proposed method detected tassels accurately and outperforms the baseline methods. It also aids advantage in the process of automation of agriculture crop-monitoring.

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IITH Creators:

IITH Creators	ORCiD
Rajalakshmi, P	UNSPECIFIED
Desai, U B	UNSPECIFIED

Item Type:

Conference or Workshop Item (Paper)

Uncontrolled Keywords:

Agriculture crops; Baseline methods; Crop monitoring; Focus of researches; Growth monitoring; Labor intensive; Multispectral images; Performance analysis;Agricultural robots; Antennas; Cell proliferation; Facsimile; Infrared devices; Remote sensing; Unmanned aerial vehicles (UAV)

Subjects:

Electrical Engineering

Divisions:

Department of Electrical Engineering

Depositing User:

. LibTrainee 2021

Date Deposited:

09 Jul 2021 09:09

Last Modified:

18 Feb 2022 06:30

URI:

http://raiithold.iith.ac.in/id/eprint/8193