<![CDATA[An unmanned aerial vehicle (UAV), commonly known as a drone, could be utilized to detect a moving object in real-time. However, there are some issues in detection process of moving object in UAV, called constraint uncertainty factor (UCF), such as environment, type of object, illumination, camera of UAV, and motion. One of practical problems that become concern of researcher in the past few years is motion analysis. Motion of an object in each frame carries a lot of information about the pixels of moving objects which has an important role as the image descriptor. In this paper, segmentation using edgebased dilation (SUED) algorithm is used to detect moving objects. The concept of the SUED algorithm is combining frame difference and segmentation process to obtain optimal results. The simulation results show the performance improvement of SUED algorithm using combination of wavelet and Sobel operator on edge detection: the number of frames for a true positive increased by 41 frames, then the false alarm rate decreased to 7% from 24% when only using Sobel operator. The combination of these two methods can also minimize noise region that affect detection and tracking process. The simulation results for tracking moving objects by Kalman filter show that there is decreasing of error between detection and tracking process.]]>
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