Browse > Article
http://dx.doi.org/10.14372/IEMEK.2019.14.3.157

Development of a Pixel-based Area Measurement Program Using Drone and Camera Module  

Kim, Jung Hwan (Semyung University)
Kim, Shik (Semyung University)
Publication Information
Abstract
As the drone industry has grown greatly in recent years, drones are being used or developed in many industrial fields such as image shooting, pesticide application, delivery service, food delivery etc. In this paper, therefore, we developed a program that takes a user's desired area at a certain height using a camera-equipped drone and obtains the area of the zone the user wants through image processing. The first user selects an area or a path. Afterwards, the drone flies and takes pictures, and then measures the user's needs. A digital image taken at a constant height and with the same resolution is composed of pixels, the area can be calculated easily if we know the number of pixels in the zone the user wants. Particularly, it is easy to calculate the area of various shaped zones, not terrain shapes such as triangles and squares. In addition, the total area of specific places of the entire zone can be calculated. With the program of this paper, anyone can easily calculate the area of the place the user wants using a drone rather than calculating the area through difficult formulas or specialized equipment.
Keywords
Drone; Image processing; Autonomous flight; Area measurement; Pixel;
Citations & Related Records
연도 인용수 순위
  • Reference
1 S. Kim, J. Kim, "Autonomous-flight Drone Algorithm Using Computer Vision and GPS," Journal of IEMEK J. Embed. Sys. Appl., Vol. 11, No. 3, pp.193-200, 2016 (in Korean).
2 Republic of Korea Ministry of Land, Transport and Maritime Affairs, "Enforcement Rules of Aviation Act 112 Article," 2017 (in Korean).
3 H.M.Easlon, A.J. Bloom, "Easy Leaf Area: Automated Digital Image Analysis for Rapid and Accurate Measurement of Leaf Area," Journal of Applications in Plant Sciences, Vol. 2, No. 7, 2014.
4 J. Kim, S. Kim, "The Autonomous Flight System Development of Drones for Nectar Source Navigation Based on Real Time Image Processing," Semyung Univ., Ph.D, 2016
5 J. J. Lugo, authorAndreas Zell, "Framework for Autonomous On-board Navigation with the AR.Drone," Journal of Intelligent and Robotic Systems, Vol. 73, No. 1, pp. 401-412, Jan 2014   DOI
6 W. Park, J. Choi, S. Choi, N. Hwang, H. Kim, "Real-Time Shooting Area Analysis Algorithm of UAV Considering Three-Dimensional Topography," Journal of Korean Institute of Communications and Information Sciences, Vol. 38, No. 12, pp. 1196-1206, 2013 (in Korean).
7 Piazzo, Lorenzo, "Image Estimation in the Presence of Irregular Sampling, Noise, and Pointing Jitter," Journal of IEEE Transactions on Image Processing, Vol. 28, No. 2, pp. 713-722, Feb 2019   DOI
8 M.J. Grinsven, B. Ginneken, C.B. Hoyng, T. Theelen, C.I. Sanchez, "Fast Convolutional Neural Network Training Using Selective Data Sampling: Application to Hemorrhage Detection in Color Fundus Images," Journal of IEEE Transactions on Medical Imaging, Vol. 35, No. 5, pp. 1273-1284, 2016.   DOI
9 A. Dave, A.K. Vadathya, R. Subramanyam, R. Baburajan, K. Mitra, "Solving Inverse Computational Imaging Problems Using Deep Pixel-Level Prior," Journal of IEEE Transactions on Computational Imaging, Vol. 5, No. 1, pp. 37-51, 2019.   DOI