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2018 | OriginalPaper | Buchkapitel

Applying Image Processing Technology to Region Area Estimation

verfasst von : Yi-Nung Chung, Yun-Jhong Hu, Xian-Zhi Tsai, Chao-Hsing Hsu, Chien-Wen Lai

Erschienen in: Genetic and Evolutionary Computing

Verlag: Springer Singapore

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Abstract

This paper proposes a method to measure a region area of field by using aerial images. An unmanned aerial vehicle (UAV) and image processing technology is used to capture images of the land and measure its area. The main advantage of using UAV to capture images is the higher degree of freedom; it can accord user’s operation to capture from various angles and heights to obtain more diversified information. Even taking pictures of a dangerous area, the user can remote the UAV in a safer place, and get the information of the area or the UAV in real time. In the experiment, an UAV is used to get images of the playground grassland which region area is known, and capture a group of images with same area from 70 to 120 m height every ten meters. In image processing process, edge detection and morphology are used to find the range of the interest region, and then count the number of pixels of it. We can get the relation between the different height and per pixels of the real area. Experimental results show that the average deviations of estimating unknown area are less than 2%.

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Metadaten
Titel
Applying Image Processing Technology to Region Area Estimation
verfasst von
Yi-Nung Chung
Yun-Jhong Hu
Xian-Zhi Tsai
Chao-Hsing Hsu
Chien-Wen Lai
Copyright-Jahr
2018
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-6487-6_10

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