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RISS 인기검색어
- 검색키워드
- 저자 : Swarup Anushka (검색결과 2 건)
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Strawberry Plant Wetness Detection Using Color and Thermal Imaging
Swarup Anushka,이원석,Peres Natalia,Fraisse Clyde 한국농업기계학회 2020 바이오시스템공학 Vol.45 No.4
Purpose Leaf wetness is the presence of free water on the surface of a crop canopy. It is mainly caused due to factors such as rainfall, dew, and irrigation. The duration for which water is present on the crop surface is called the leaf wetness duration (LWD). The relationship between leaf wetness and plant disease has been studied for centuries. It has been found that the rate of infection is directly linked to the temperature of plants during the wet periods. Thus, it is imperative to detect and monitor the presence of water on the plant surface. Methods Currently, the most popular solution for this purpose is to use electronic leaf wetness sensors which are difficult to calibrate and are not user friendly. This research aimed at detecting leaf wetness in strawberry plants using noninvasive optical methods such as color and thermal imaging. Results It was found that color imaging yielded good classification results for differentiating between wet and dry leaf surfaces. However, its dependence on illumination conditions was a drawback. Thermal imaging proved to be useful when using highresolution cameras for water droplet detection but was dependent on ambient weather conditions. Conclusion The results suggested that fusing color and thermal imaging technologies could compensate for the drawbacks present when using these technologies individually and could prove to be potent in detecting leaf wetness.
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Vision based rail track extraction and monitoring through drone imagery
Arun Kumar Singh,Anushka Swarup,Ankush Agarwal,Dharmendra Singh 한국통신학회 2019 ICT Express Vol.5 No.4
Track detection and gauge measurement are considered as crucial aspects of railway inspection systems. Traditionally, monitoring by human inspectors was done. Nowadays, computer vision-based systems are used due to their flexibility and ease of use. In recent years, various prototypes of vision based inspection system have been proposed, most have a camera mounted on carts or trains. Employing drones for such monitoring systems provides a cost effective and accurate means for monitoring tracks. This paper explores the possibilities of computer vision based monitoring through drone imagery. The experimental results ensure that the proposed method provides high reliability and accuracy.
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