A Comparison of Edge Detection Algorithms in Aerial Images
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Abstract
Image analysis is becoming increasingly significant in a variety of industries, including agriculture, medicine, security, surveillance, observation and etc. The image analysis is still processed by humans. This is quite costly and time consuming. For improving image analysis, an image analysis algorithm is required. The edge detection is one of the most significant aspects of image analysis. In this research, various edge detection algorithms are compared and applied to aerial images captured by unmanned aerial vehicles (UAV). PR (Ratio of true to false edges), PSNR (Peak signal to noise ratio), and F-Measure are used to evaluate and analyze the results. The overall goal of this study is to gain a better knowledge of how each edge detection algorithm performs with the UAV aerial images.
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