Applying image processing technology to region area estimation

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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%.

Original languageEnglish
Title of host publicationGenetic and Evolutionary Computing - Proceedings of the 11th International Conference on Genetic and Evolutionary Computing
EditorsShu-Chuan Chu, Jerry Chun-Wei Lin, Chien-Ming Chen, Jeng-Shyang Pan
PublisherSpringer Verlag
Pages77-83
Number of pages7
ISBN (Print)9789811064869
DOIs
Publication statusPublished - 2018 Jan 1
Event11th International Conference on Genetic and Evolutionary Computing, 2017 - Kaohsiung, Taiwan
Duration: 2017 Nov 62017 Nov 8

Publication series

NameAdvances in Intelligent Systems and Computing
Volume579
ISSN (Print)2194-5357

Other

Other11th International Conference on Genetic and Evolutionary Computing, 2017
CountryTaiwan
CityKaohsiung
Period17-11-0617-11-08

Fingerprint

Unmanned aerial vehicles (UAV)
Image processing
Pixels
Edge detection
Antennas
Experiments

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Chung, Y-N., Hu, Y. J., Tsai, X. Z., Hsu, C. H., & Lai, C. W. (2018). Applying image processing technology to region area estimation. In S-C. Chu, J. C-W. Lin, C-M. Chen, & J-S. Pan (Eds.), Genetic and Evolutionary Computing - Proceedings of the 11th International Conference on Genetic and Evolutionary Computing (pp. 77-83). (Advances in Intelligent Systems and Computing; Vol. 579). Springer Verlag. https://doi.org/10.1007/978-981-10-6487-6_10
Chung, Yi-Nung ; Hu, Yun Jhong ; Tsai, Xian Zhi ; Hsu, Chao Hsing ; Lai, Chien Wen. / Applying image processing technology to region area estimation. Genetic and Evolutionary Computing - Proceedings of the 11th International Conference on Genetic and Evolutionary Computing. editor / Shu-Chuan Chu ; Jerry Chun-Wei Lin ; Chien-Ming Chen ; Jeng-Shyang Pan. Springer Verlag, 2018. pp. 77-83 (Advances in Intelligent Systems and Computing).
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Chung, Y-N, Hu, YJ, Tsai, XZ, Hsu, CH & Lai, CW 2018, Applying image processing technology to region area estimation. in S-C Chu, JC-W Lin, C-M Chen & J-S Pan (eds), Genetic and Evolutionary Computing - Proceedings of the 11th International Conference on Genetic and Evolutionary Computing. Advances in Intelligent Systems and Computing, vol. 579, Springer Verlag, pp. 77-83, 11th International Conference on Genetic and Evolutionary Computing, 2017, Kaohsiung, Taiwan, 17-11-06. https://doi.org/10.1007/978-981-10-6487-6_10

Applying image processing technology to region area estimation. / Chung, Yi-Nung; Hu, Yun Jhong; Tsai, Xian Zhi; Hsu, Chao Hsing; Lai, Chien Wen.

Genetic and Evolutionary Computing - Proceedings of the 11th International Conference on Genetic and Evolutionary Computing. ed. / Shu-Chuan Chu; Jerry Chun-Wei Lin; Chien-Ming Chen; Jeng-Shyang Pan. Springer Verlag, 2018. p. 77-83 (Advances in Intelligent Systems and Computing; Vol. 579).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - 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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Chung Y-N, Hu YJ, Tsai XZ, Hsu CH, Lai CW. Applying image processing technology to region area estimation. In Chu S-C, Lin JC-W, Chen C-M, Pan J-S, editors, Genetic and Evolutionary Computing - Proceedings of the 11th International Conference on Genetic and Evolutionary Computing. Springer Verlag. 2018. p. 77-83. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-981-10-6487-6_10