In order to enhance the speed and accuracy of ellipse detection, an ellipse detection algorithm based on edge classification is proposed. Too many edge points are removed by making edge into point in serialized form and the distance constraint between the edge points. It achieves effective classification by the criteria of the angle between the edge points. And it makes the probability of randomly selecting the edge points falling on the same ellipse greatly increased. Ellipse fitting accuracy is significantly improved by the optimization of the RED algorithm. It uses Euclidean distance to measure the distance from the edge point to the elliptical boundary. Experimental results show that: it can detect ellipse well in case of edge with interference or edges blocking each other. It has higher detecting precision and less time consuming than the RED algorithm.
KEYWORDS: Target detection, Signal to noise ratio, Computer programming, Aerospace engineering, Surveillance systems, Image processing, Digital breast tomosynthesis, Computer simulations, Sensors, Detector development
With the development of Space Technology, the demand to Space Surveillance System is more urgent than before. The paper studies the dim and small target of long range. Firstly, it describes the research status of dim and small target abroad and the two detection principle of DBT and TBD. Secondly, it focuses on the higher-order correlation method, dynamic programming method and projection transformation method of TBD. Finally, it studies the image sequence simulation of different signal to noise ratio (SNR) with the real-time data from the aircraft in orbit. The image sequence is used to experimental verification. The test results show the dim and small target detection capability and applicable occasion of different methods. At the same time, it provides a new idea to the development of long-distance optical detector.
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