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  • 한국과학기술정보연구원(KISTI) 서울분원 대회의실(별관 3층)
  • 2024년 07월 03일(수) 13:30
 

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Automatic Counting of Rice Plant Numbers After Transplanting Using Low Altitude UAV Images

INTERNATIONAL JOURNAL OF CONTENTS / INTERNATIONAL JOURNAL OF CONTENTS, (P)1738-6764; (E)2093-7504
2017, v.13 no.3, pp.1-8
https://doi.org/10.5392/IJoC.2017.13.3.001
Md Nasim Reza (전남대학교)
나인섭 (전남대학교)
이경환 (전남대학교)

Abstract

Rice plant numbers and density are key factors for yield and quality of rice grains. Precise and properly estimated rice plant numbers and density can assure high yield from rice fields. The main objective of this study was to automatically detect and count rice plants using images of usual field condition from an unmanned aerial vehicle (UAV). We proposed an automatic image processing method based on morphological operation and boundaries of the connected component to count rice plant numbers after transplanting. We converted RGB images to binary images and applied adaptive median filter to remove distortion and noises. Then we applied a morphological operation to the binary image and draw boundaries to the connected component to count rice plants using those images. The result reveals the algorithm can conduct a performance of 89% by the F-measure, corresponding to a Precision of 87% and a Recall of 91%. The best fit image gives a performance of 93% by the F-measure, corresponding to a Precision of 91% and a Recall of 96%. Comparison between the numbers of rice plants detected and counted by the naked eye and the numbers of rice plants found by the proposed method provided viable and acceptable results. The R2 value was approximately 0.893.

keywords
Rice Plant, Low Altitude Image, UAV, Morphological Operation, Connected Component

INTERNATIONAL JOURNAL OF CONTENTS